Assessing Aflatoxin Knowledge, Perceptions, and related Practices, in a Rural Coastal Community: A Population-Based Cross-sectional Survey

Assessing Aflatoxin Knowledge, Perceptions, and related Practices, in a Rural Coastal Community: A Population-Based Cross-sectional Survey | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing Aflatoxin Knowledge, Perceptions, and related Practices, in a Rural Coastal Community: A Population-Based Cross-sectional Survey Rosebella Iseme-Ondiek, Joseph Abuodha, Anthony Ngugi, Innocent Abayo, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8785894/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract BACKGROUND Aflatoxin contamination is a significant yet under-addressed food safety challenge in low-resource settings, driven by a complex interplay of environmental, agricultural, and socio-economic factors. Limited access to agricultural inputs, inadequate post-harvest handling and storage, and weak regulatory enforcement alongside food scarcity and climate change heighten the risk of contamination and exposure. Human exposure is associated with serious health consequences, including hepatocellular carcinoma, immune suppression, and childhood stunting. Although aflatoxin is increasingly recognized as a global food safety concern, little is known about community-level knowledge, risk perceptions, and preventive practices. This study examined household heads’ awareness, perceptions, and behaviours related to aflatoxin exposure and mitigation in a rural coastal community in Kenya. METHODS We conducted a cross-sectional survey using a census approach within the Kaloleni-Rabai Health and Demographic Surveillance System (KRHDSS). Between July and December 2022, data were collected from 17,813 household heads through face-to-face, interviewer-administered, digitized questionnaires. RESULTS Farming was the predominant occupation (n = 5,757; 32.3%). Maize was sourced primarily from household harvests and local markets, with over three-quarters (n = 13,818; 77.6%) of respondents consuming maize flour three or more times weekly. Despite maize being a dietary staple, awareness of aflatoxin was limited: only 49.5% (n = 8,816) had heard of aflatoxin. Even fewer (< 20%) respondents were able to identify foods at risk, signs of contamination, causes of fungal growth, or health consequences of exposure. Socio-economic status, rurality, education, and sex influenced aflatoxin-related knowledge, perceptions, and practices. CONCLUSION Low awareness of aflatoxin constrains rural households’ ability to prevent contamination and limit exposure. As aflatoxin risk arises at multiple points along the agricultural value chain, and vulnerability to exposure is heightened during periods of food scarcity, comprehensive approaches are required. Effective prevention will depend on integrated strategies that combine educational initiatives, infrastructural support, and policy interventions targeting agricultural practices, food security, and consumer behaviours. Aflatoxin Population-based survey Rural community Health risks Cancer risks KEY MESSAGE What is already known about this topic? Aflatoxin contamination is a major yet under-addressed food safety challenge in low-resource settings. In the absence of analytical methods for community-level detection of aflatoxin exposure, low-cost household surveillance approaches capable of estimating exposure risks at the community level can be highly informative. What does this study add? The limited awareness of aflatoxin in our study population (particularly among rural residents, poorer households, and individuals without formal education) suggests the presence of poorly implemented control measures to mitigate contamination and reduce exposure. Maize is consumed frequently establishing a pathway for chronic aflatoxin exposure. How might these findings affect research, practice, or policy? These findings signal an urgent need to prioritize aflatoxin prevention by investing in surveillance and embedding community education into agricultural and health programs. BACKGROUND Aflatoxins are naturally occurring toxins produced by certain fungi, most importantly Aspergillus flavus ( A. flavus ) and Aspergillus parasiticus ( A. parasiticus )(1). Aflatoxins contaminate many African dietary staples such as maize and maize products, groundnuts and its produce as well as other legumes and oilseeds, rice, cassava, sorghum, millet, and yams (1,2). They have also been reported in herbal products(2). Contamination occurs under certain conditions, namely, dry weather near crop maturity, high moisture during harvest, and inadequate drying and storage of crops(1). If aflatoxin-contaminated crops are consumed by humans, aflatoxin poisoning (i.e. aflatoxicosis) can occur. Acute aflatoxin toxicity may result in nausea, vomiting, abdominal pain, convulsions, and other signs of acute liver injury(3). Importantly, chronic exposure to even low levels of contamination in crops consumed regularly increases the risk of liver cancer and can suppress the immune system(4). Exposure to high levels of aflatoxin can be fatal(4). Aflatoxins can also enter the human diet through livestock products if the livestock are given contaminated feed(5). Consequently, exposure can also occur through consumption of animal products such as blood, eggs, ghee, meat, milk, and dairy products. Children can also be affected through breast milk or direct consumption of weaning foods, extending the risk of negative health impacts to very young populations(6,7). Exposure to aflatoxins can also occur through dust inhalation during processing of contaminated crops and feeds(8). The toxins can also permeate the skin as well as cause foetal exposure in-utero (aflatoxin is known to cross the placenta)(8,9). Existing literature also suggests an association between aflatoxin exposure and child growth stunting(10). As such, aflatoxin constitutes a significant public health concern. Typically, many rural African communities, rely heavily on agriculture, employing about 70% of their populations(11). The reliance on semi-subsistence farming, devoid of centralized food systems, leaves inhabitants vulnerable to aflatoxin exposure due to inadequate infrastructure for monitoring food and feed safety(2). This risk is further exacerbated by the lack of irrigation, as well as improper drying and storage facilities(12). Notably, the prevalence of aflatoxin contamination is increasing across Africa, driven in part by the growing impacts of climate change(13). Importantly, cereals and legumes vulnerable to aflatoxin contamination, which serve as dietary staples in many rural households, are also commonly used in weaning and complementary feeding for infants and young children(2). This unique blend of environmental and socioeconomic factors significantly heightens the risk of aflatoxin contamination and subsequent exposure among the region’s population, beginning early in life. In Kenya, aflatoxins are widely recognized as a persistent problem(14). However, a nationally representative cross-sectional serosurvey which analysed serum specimens for aflatoxin levels, revealed marked regional variations in exposure(15). In this study, the Coast region ranked second highest, highlighting the urgent need for targeted studies whose findings may guide interventions in this high-risk area. A. flavus , is considered the primary producer of aflatoxins affecting Kenya’s agricultural commodities, and it thrives in conditions mirroring those found in Kilifi County, one of the nation's five coastal counties(14). Kilifi County is characterised by an erratic tropical climate comprising periodic droughts, high humidity, and high temperatures, conducive to A. flavus growth(16). Kilifi County also grapples with socioeconomic challenges, including high poverty rates (71% rate of absolute poverty compared to the national average of 47%) and low education levels, alongside a population predominantly composed of smallholder farmers where over 50% of the county’s inhabitants derive their livelihoods from crop and livestock production(16,17). In addition, maize, cowpea, cassava, and nuts (all aflatoxin susceptible crops) are amongst the key staples grown and consumed in the County(18). Since aflatoxin contamination cannot be visually detected without specialized tools, Knowledge, Perceptions, and Practice (KPP) surveys provide a cost-effective means of assessing population-level exposure risks in resource-limited settings. In the absence of affordable community-level analytical methods, household surveys yield valuable insights to guide targeted mitigation measures. We therefore conducted a population-based survey among household heads in a predominantly agricultural rural coastal community to evaluate knowledge, perceptions, and practices related to aflatoxin. Specifically, the survey assessed whether vulnerable farming households recognize foods prone to contamination, understand the causes and signs of aflatoxin, and are aware of prevention strategies. This is critical, as evidence consistently shows that populations with stronger awareness of health risks and preventive measures are more likely to adopt protective practices(19,20). The findings will inform the development of interventions to mitigate aflatoxin exposure in Kilifi as well as other similarly affected settings. MATERIALS AND METHODS Study design and objectives A cross-sectional population-based survey (nested in an existing surveillance platform) was utilized to assess the knowledge, perceptions and practices pertaining to aflatoxin contamination, associated health risks and prevention amongst household heads of a rural coastal community. Data were collected between July and December 2022. Study setting, study participants and sampling The study was undertaken in the largely rural areas of southern Kilifi, one of five coastal counties in Kenya. The Department of Population Health at Aga Khan University in collaboration with the local health department operates a health and demographic surveillance system, that tracks approximately 103,000 inhabitants of two sub-counties (Kaloleni and Rabai) within this area. This ongoing endeavour employs the use of distinct identifiers that enables longitudinal monitoring of all individuals enumerated within the surveillance platform. The study area, its population, and the surveillance platform have been comprehensively described in previous publications(21,22). Of note, roughly 70% of the populace resides below the poverty threshold, with 81% dependent on subsistence agriculture, crafts, sporadic employment, and small-scale trading to sustain their livelihoods(21). The target population for this survey were household heads of all households that form part of the Kaloleni Rabai Health and Demographic Surveillance System (KRHDSS). A census approach (targeting 100% inclusion of all household heads) was used, with all household heads invited to participate in the study through household visits by trained community health promoters (CHPs). The CHPs serve as a cohesive network of community resource personnel responsible for gathering surveillance data and providing household-level health education and health promotion(23). Therefore, they were well-positioned to conduct the aflatoxin survey during routine surveillance data collection. A total of 20,502 household heads were targeted for inclusion in this study. Data collection tools and approaches Data were collected by trained CHPs using face-to-face electronic interviewer administered questionnaires. The latter underwent training over a week-long period, which encompassed role-playing scenarios as well as piloting the data collection tools in the field before commencing the actual data collection. After the role-play and piloting exercises, necessary modifications and correction took place to ensure reliability and validity of the data collection tool. The semi-structured questionnaires were originally designed in paper form and thereafter digitized and deployed on electronic data collection tablets. Electronic data capture enabled direct uploads from the field to a web-based database and real-time checking for data quality. The data collection tool included inquiries regarding sociodemographic traits of household heads (such as age, sex, education, and occupation), medical history, assets owned and frequency of consuming foods susceptible to aflatoxin contamination. It also delved into the origins of such foods, awareness levels concerning aflatoxin, knowledge regarding signs and causes of contamination, transmission modes, and health repercussions. Additionally, it explored perceptions toward its significance and strategies employed to safeguard households from exposure. The full questionnaire is available in Supplementary File 1. Data management and analysis Quantitative data analysis was undertaken using STATA version 13 (StataCorp. 2013)(24). Data in Comma-Separated Values (CSV) format was extracted from the database and directly imported into STATA. Duplicate entries were erased, and any erroneous responses and missing data identified and rectified through a re-survey of the household head. The variables of interest were either continuous or categorical measures. Descriptive statistics, including means, standard deviations (SD), frequencies, and percentages, were employed to elucidate the distribution of knowledge, perceptions, and practices within our study cohort. Aflatoxin knowledge was operationalized as a composite score derived from responses to six domains, i.e., foods at risk, signs and modes of contamination, causes of contamination, control measures and health effects of aflatoxin exposure. Correct responses were summed to generate a continuous knowledge score (range 0–19). Principal component analysis was carried out to develop a five-point asset-based socioeconomic status (wealth index) scale using the Demographic and Health Surveillance (DHS) Wealth Index approach and data generated from the household-based interviews with household heads. The first principal component was used to define the asset index. Households were divided into five wealth quintiles (from poorest to wealthiest) based on the composite wealth index score. DHS wealth quintiles are widely used across several health areas for examining health outcomes by wealth status in low- and middle- income countries (LMICs) to understand patterns of service utilisation, inequalities and disparities. Regression (linear and logistic as appropriate) was carried out to find the contribution of predefined independent variables to household head knowledge, perceptions and practices related to aflatoxin as appropriate. In order to address missing socio-economic status (SES) data, analyses were conducted using both complete-case analysis (CCA) and multiple imputation (MI). CCA included only participants with complete information for all variables, while MI used chained equations to generate 20 imputed datasets under the assumption of data missing at random. The latter assumption meant that the probability of missingness was related to observed variables in the dataset but not to the unobserved values themselves. This assumption was considered reasonable in this study because patterns of missingness were plausibly explained by measured participant characteristics (, i.e., age, sex, place of residence, school attendance, level of knowledge of aflatoxin, frequency of consumption of maize meal, and consideration of aflatoxin when making food purchases) as evidenced by the findings of bivariate analyses ( Appendix 1 ). A single analysis model was applied across all imputed datasets, with estimates pooled using Rubin’s rules to incorporate both within- and between-imputation variability. Results from both approaches (CCA and MI) were compared to assess the potential impact of missing data on effect estimates and statistical significance (set at p < 0.05). Ethical considerations The proposal obtained clearance from the Institutional Scientific and Ethics Review Committee at Aga Khan University (Approval No: 2013/REC-65(version10)). Furthermore, a research permit was granted by the National Commission for Science, Technology, and Innovation (License No: NACOSTI/P/22/18630). Subsequently, necessary approvals were obtained from the county offices, and informed consent was acquired from each study participant. Various measures were implemented to ensure the privacy and confidentiality of respondents including the use of unique anonymous identifiers, and limiting data access to authorised persons only, which was safeguarded by password protection. RESULTS The aflatoxin household survey recorded an 86.9% (n = 17,813) response rate which is well above the 80% acceptable minimum threshold set for household surveys. Reasons for non-participation were not recorded. Out of the 17, 813 household heads who were surveyed, three-quarter were males (n = 13,342; 74.9%). In addition, amongst the 11,525 (64.7%) household heads who had received some form of formal education, the majority (n = 8,582; 74.5%) stated that primary school education was their highest level of academic achievement. Furthermore, more males than females had ever received any formal education, i.e., 75.2% versus 33.3% respectively. The mean age of household heads was approximately 49.1 (SD = 16.1) years, with female household heads being older (mean = 54.4 years, SD = 16.5 years) than male household heads (mean = 47.3, SD = 15.6 years). Additionally, the most common occupation amongst this study sample was farming (n = 5,757; 32.3%). Importantly, less than half of the study sample reported any hospital visit in the 12 months preceding the survey, regardless of whether the visit was for routine care, treatment, or screening (n = 8,223; 46.2%) (Table 1 ). Table 1 Characteristics of study respondents. Characteristic Females n = 4,471 (25.1%) Males n = 13,342 (74.9%) Total N = 17,813 (100.0%) 1. Age, mean (SD) 54.37 (16.5) 47.29 (15.6) 49.07 (16.1) 2. Formal Education (Yes), n (%) 1,489 (33.3) 10,036 (75.2) 11,525 (64.7) 3. Highest level of education attained. (n = 11,525), n (%) Primary – 1,175 (78.9) Primary – 7,407 (73.8) Primary – 8,582 (74.5) Secondary – 271 (18.2) Secondary – 2,344 (23.4) Secondary – 2,615 (22.7) Tertiary – 43 (2.9) Tertiary – 285 (2.8) Tertiary – 328 (2.8) 4. Occupation, n (%) Employed worker – 197 (4.4) Employed worker – 2,960 (22.2) Employed worker – 3,157 (17.7) Casual worker – 395 (8.8) Casual worker – 4,493 (33.7) Casual worker – 4,888 (27.4) Trader – 469 (10.5) Trader – 1,316 (9.9) Trader – 1,785 (10.0) Farmer – 2,139 (47.8) Farmer – 3,618 (27.1) Farmer – 5,757 (32.3) Housewife – 1,149 (25.7) N/A Housewife – 1,149 (6.5) Other – 122 (2.7) Other – 955 (7.2) Other – 1,077 (6.0) 5. Proportion that visited a hospital in the 12 months preceding the survey for routine care, treatment, or screening, n (%) 2,442 (54.6) 5,781 (43.3) 8,223 (46.2) 6. Proportion that had blood work done in the 12 months preceding the survey, n (%) 742 (16.6) 1,621 (12.2) 2,363 (13.3) 7. Wealth quintiles, n (%) Quintile 1 1,137 (25.4) 2,249 (16.9) 3,386 (19.0) Quintile 2 974 (21.8) 2,460 (18.4) 3,434 (19.3) Quintile 3 718 (16.1) 2,451 (18.4) 3,169 (17.8) Quintile 4 688 (15.4) 2,610 (19.6) 3,298 (18.5) Quintile 5 595 (13.3) 2,742 (20.6) 3,337 (18.7) Missing 359 (8.0) 830 (6.2) 1,189 (6.7) Overall, the level of awareness and knowledge of aflatoxin amongst this study sample was considerably low. Only half, i.e., 49.5% (95%CI: 48.8% − 50.2%) of the study population stated that they had ever heard of aflatoxin and subsequent interview questions were administered only to these. Only a few were able to identify foods that were contaminated by aflatoxin (n = 1,657; 18.8%), the signs of aflatoxin contamination (n = 1,526; 17.3%), the causes of aflatoxin contamination (n = 829; 9.4%) and the health effects associated with exposure to this toxin (none of the respondents correctly identified the complete set of listed health effects associated with aflatoxin exposure). Table 2 outlines the results from the knowledge assessments. Maize (n = 7,318; 83.0%) and wheat (n = 4,270; 48.4%) emerged as the most correctly recognized foods susceptible to aflatoxin contamination, with discoloration (n = 6,330; 71.8%) being the widely acknowledged sign of such contamination. In contrast, participants showed least awareness of a mouldy smell as an indication of aflatoxin presence, and drying maize on the ground was the least recognized cause of maize contamination with aflatoxin. The commonly known causes of contamination were poorly dried or wet maize (n = 6,445; 73.2%) and inadequate storage practices (n = 5,575; 63.2%). Moreover, liver cancer (n = 547; 6.2%) was the least identified health consequence of aflatoxin exposure, with respondents more commonly associating exposure with stunted growth in children (n = 2,751; 31.2%) and immune suppression (n = 1,874; 21.3%). Aflatoxin-related knowledge scores ranged from 1 to 19. The scores were approximately normally distributed, with a mean of 6.2 (SD = 3.1) and a median of 6 (Interquartile range: 3–8), indicating that 50% of participants scored below 6. For a detailed breakdown of responses to the knowledge questions, and the scoring methodology refer to Appendix 2 a and b , respectively. Table 2 Knowledge of Aflatoxin (n = 17,813) Knowledge questions Total - n (%) Female - n (%) Male - n (%) 1. Aware of aflatoxin. 8,816 (49.5) 1,955 (43.7) 6,861 (51.4) 2. Knowledge of foods contaminated by aflatoxin* Maize, Wheat, and Milk – 1,657 (18.8) Maize, Wheat, and Milk – 384 (19.6) Maize, Wheat, and Milk – 1,273 (18.6) I don’t know – 1,437 (16.3) I don’t know – 233 (11.9) I don’t know – 1,204 (17.6) 3. Knowledge of signs of aflatoxin contamination in maize* Discolouration, Mouldiness and wetness, Presence of insects and Mouldy smell – 1,526 (17.3) Discolouration, Mouldiness and wetness, Presence of insects and Mouldy smell – 359 (18.4) Discolouration, Mouldiness and wetness, Presence of insects and Mouldy smell – 1,167 (17.0) I don’t know – 876 (9.9) I don’t know – 167 (8.5) I don’t know – 709 (10.3) 4. Knowledge of causes of contamination of maize with aflatoxin* Poorly dried or wet maize, Poor storage of maize, Drying maize on the ground, Shelling wet maize – 829 (9.4) Poorly dried or wet maize, Poor storage of maize, Drying maize on the ground, Shelling wet maize – 168 (8.6) Poorly dried or wet maize, Poor storage of maize, Drying maize on the ground, Shelling wet maize – 661 (9.6) I don’t know – 219 (2.5) I don’t know – 62 (3.2) I don’t know – 157 (2.3) 5. Knowledge of health effects of aflatoxin exposure* Stunting in children, Immunity suppression, Liver cirrhosis, Death – 0 (0.0) Stunting in children, Immunity suppression, Liver cirrhosis, Death – 0 (0.0) Stunting in children, Immunity suppression, Liver cirrhosis, Death – 0 (0.0) I don’t know – 1,325 (15.0) I don’t know – 412 (21.1) I don’t know – 913 (13.3) 6. Aflatoxin can be transmitted through breast milk and contaminated chicken meat. * (Yes) 1,614 (18.3) 345 (17.7) 1,269 (18.5) 7. Aflatoxin can be destroyed through processes like cooking, boiling, and baking. * (No) 3,843 (43.6) 855 (43.7) 2,988 (43.6) *Responses to knowledge questions are only among those who stated they were aware of aflatoxin. Results are presented for respondents who identified all correct answers and for those who explicitly stated they did not know the correct answer. See appendix 2 for detailed breakdown of responses to the knowledge questions. Only participants that were aware of aflatoxin were asked to answer questions regarding their perceptions of this contaminant. The results showed that more than half (n = 5,353; 60.8%) of participants who were aware of aflatoxin, considered it when making flour purchases. Amongst respondents who did consider aflatoxin when purchasing flour, the communication on the packaging was the frequently reported strategy (n = 2,633; 49.1%) used to determine whether flour was ‘aflatoxin safe’. In this regard, participants relied on the presence of the Kenya Bureau of Standards (KEBS) mark of quality as the sought after indicator of safety. Interestingly, almost a third (n = 2,574; 29.2%) of the respondents believed there were Kenyan maize brands that were considered aflatoxin safe. When all study respondents (irrespective of awareness of aflatoxin) were asked what could be done to create more awareness around aflatoxin safe maize flour, a greater portion of study respondents (n = 9,128; 51.2%) stated communication (either through Radio, Television and Billboards) should be undertaken. Regarding aflatoxin-related practices, most respondents (n = 13,818; 77.6%) consumed maize meal three or more times a week. Similarly, most respondents (n = 12,346; 69.3%) consumed maize meal that is locally farmed and stored (Table 3 ). Table 3 Perceptions and Practices related to Aflatoxin. Perception Statements Females - n (%) Males – n (%) Total - n (%) *Proportion that considers aflatoxin while purchasing maize flour. (females = 1,955; males = 6,861) 1,159 (59.3) 4,204 (61.3) 5,363 (60.8) ⁺Strategies used to determine flour is aflatoxin safe. (females = 1,159; males = 4,204) ⁺Rely on word of mouth 330 (28.5) 1,322 (31.4) 1,652 (30.8) ⁺Communication on package 586 (50.6) 2,047 (48.7) 2,633 (49.1) ⁺Communication from media outlets 243 (21.0) 835 (19.9) 1,078 (20.1) *Proportion that believes there are Kenyan maize brands that are aflatoxin safe. (females = 1,955; males = 6,861) 546 (27.9) 2,028 (29.6) 2,574 (29.2) Measures that should be taken to create more awareness around aflatoxin safe maize flour. (females = 4,472; males = 13,342) Advocacy 618 (13.8) 1525 (11.4) 2143 (12.0) Communication- Radio, Television, Billboards 2145 (48.0) 6983 (52.3) 9128 (51.2) Endorsement by medical experts 1388 (31.0) 4245 (31.8) 5633 (31.6) Other 320 (7.2) 587 (4.4) 907 (5.1) Aflatoxin related practices (females = 4,471; males = 13,342) Proportion of household heads consuming ugali (maize meal) ≥3X/Week 3,475 (77.7) 10,343 (77.5) 13,818 (77.6) Proportion of household heads that consume maize meal that is locally farmed and stored. 2,876 (64.3) 9,470 (71.0) 12,346 (69.3) Proportion of household heads that consume maize meal that is pre-packed. 3,486 (78.0) 10,826 (81.1) 14,312 (80.4) *Responses to questions on whether they consider aflatoxin while purchasing maize flour and whether there are available Kenyan maize brands that are aflatoxin safe are only among those who stated they were aware of aflatoxin (n = 8,816). ⁺The question regarding how respondents determine aflatoxin is safe was answered ONLY by respondents who stated they considered aflatoxin when purchasing flour. ⁺ Respondents answering this question were able to pick multiple responses. All 17,813 respondents answered the question regarding what could be done to create more awareness as well as aflatoxin practice related questions. A total of 6.7% (n = 1,189) of households had missing household asset data and, consequently, no assigned wealth quintile (Table 1 ). A comparison of results from the complete case analysis - CCA ( Appendix 3 ) and the estimates generated using the imputed data (Table 4 ) yielded similar findings. Rural residency (Imputed findings - A_OR = 1.9, 95% CI: 1.8–2.1 ) , and higher SES (Imputed findings Quintile 4 - A_OR = 1.1, 95% CI: 1.0–1.3; Imputed findings Quintile 5 - A_OR = 1.3, 95% CI: 1.2–1.5 ) , were significantly associated with increased odds of consuming maize meal three or more times per week, whilst consumption of pre-packed maize meal (when compared with maize meal that is locally milled) showed a modest reduced odds (Table 4 a and Appendix 3a ). Similarly, rural residency (Imputed findings - A_OR = 1.1, 95% CI: 1.1–1.2 ) , school attendance (Imputed findings - A_OR = 1.4, 95% CI: 1.3–1.5 ) , and higher SES (Imputed findings Quintile 5 - A_OR = 1.1, 95% CI: 1.0–1.3 ) were positively associated with considering aflatoxin when making household food purchases. In addition, greater aflatoxin-related knowledge was also found to increase the odds of considering aflatoxin during household food purchase decisions as well as consuming maize meal three or more times per week, across both analyses (Table 4 b and Appendix 3b ). Notably, aflatoxin-related knowledge was higher among those who had ever attended school (Imputed findings - A_β = 0.6, 95% CI: 0.5–0.7 ) , but lower among those residing in rural areas ( Imputed findings - A_β = -0.9, 95% CI: -1.0 – -0.8). Furthermore, female household heads (Imputed findings - A_β = -0.2, 95% CI: -0.3 – -0.1 ) demonstrated lower levels of aflatoxin-related knowledge compared to their male counterparts. In addition, while the imputed dataset showed a statistically significant association between all SES quintiles and aflatoxin-related knowledge, the CCA indicated significance only in the highest quintile. Nonetheless a similar trend was observed across both analyses whereby aflatoxin-related knowledge increased with increasing wealth (Table 4 c and Appendix 3c ). Table 4 Factors associated with Aflatoxin related Knowledge, Perceptions and Practices (analyses using imputed SES data). (a) Household Characteristics Unadjusted OR; 95% CI P value Adjusted OR; 95% CI P value a. Proportion of household heads consuming ugali (maize meal) ≥3X/Week (logistic regression). 1. Age of household head. 0.999 (0.998–1.000) 0.419 0.999 (0.998–1.001) 0.333 2. Sex of household head. Reference – Male 1 1 3. Sex of household head (Female). 1.010 (0.931–1.096) 0.803 0.996 (0.911–1.089) 0.923 4. Residential status household. Reference – Peri-urban 1 1 5. Residential status household (Rural). 1.988 (1.851–2.136) 0.000 1.947 (1.806–2.098) 0.000 6. Household head received formal education. Reference – No 1 1 7. Household head received formal education (Yes). 0.925 (0.860–0.997) 0.040 0.994 (0.915–1.080) 0.890 8. Socioeconomic status of household. Quintile 2 Quintile 3 Quintile 4 Quintile 5 Reference – Quintile 1 1 1 1.090 (0.981–1.211) 0.109 1.009 (0.906–1.124) 0.867 1.067 (0.958–1.188) 0.237 1.050 (0.941–1.172) 0.385 1.109 (0.997–1.234) 0.058 1.142 (1.023–1.275) 0.018 1.150 (1.033–1.281) 0.011 1.322 (1.181–1.480) 0.000 9. Level of knowledge of aflatoxin of household head. 0.922 (0.912–0.932) 0.000 0.936 (0.925–0.946) 0.000 10. Maize meal consumed is pre-packed or milled locally. Reference – Milled locally 1 1 11. Maize meal consumed is pre-packed or milled locally (pre-packed). 1.002 (0.917–1.095) 0.964 0.989 (0.819–0.985) 0.022 * U_OR – Unadjusted odds ratio; A_OR – Adjusted odds ratio; 95% CI – 95% Confidence Interval. (b) Household Characteristics U_OR; 95% CI P value A__OR; 95% CI P value b. Proportion of household heads that consider aflatoxin when making household food purchases (logistic regression). 1. Age of household head. 1.000 (0.999–1.001) 0.886 1.000 (0.998–1.001) 0.609 2. Sex of household head. Reference – Male 1 1 3. Sex of household head (Female) 0.804 (0.749–0.863) 0.000 1.034 (0.950–1.126) 0.436 4. Residential status of household. Reference – Peri-urban 1 1 5. Residential status of household (Rural) 0.800 (0.753–0.850) 0.000 1.136 (1.059–1.217) 0.000 6. Household head received formal education. Reference – No 1 1 7. Household head received formal education (Yes). 1.644 (1.541–1.755) 0.000 1.388 (1.282–1.502) 0.000 8. Socioeconomic status of household. Quintile 2 Quintile 3 Quintile 4 Quintile 5 Reference – Quintile 1 1 1 0.945 (0.862–1.036) 0.228 0.993 (0.897–1.099) 0.887 0.920 (0.837–1.011) 0.082 0.921 (0.829–1.023) 0.126 1.024 (0.934–1.124) 0.609 0.975 (0.879–1.082) 0.638 1.371 (1.252–1.501) 0.000 1.145 (1.032–1.271) 0.010 9. Level of knowledge of aflatoxin of household head. 1.365 (1.349–1.381) 0.000 1.361 (1.345–1.378) 0.000 * U_OR – Unadjusted odds ratio; A_OR – Adjusted odds ratio; 95% CI – 95% Confidence Interval. (c) Household Characteristics U_β; 95% CI P value A_β; 95% CI P value c. Aflatoxin related knowledge score amongst household heads (linear regression). 1. Age of household head 0.001 (-0.001–0.003) 0.468 0.000 (-0.002–0.002) 0.978 2. Sex of household head Reference – Male 1 1 3. Sex of household head (Female) -0.453 (-0.559 – -0.347) 0.000 -0.186 (-0.299 – -0.073) 0.001 4. Residential status of household Reference – Peri-urban 1 1 5. Residential status of household (Rural) -0.997 (-1.089 – -0.906) 0.000 -0.904 (-0.996 – -0.812) 0.000 6. Household head received formal education Reference – No 1 1 7. Household head received formal education (Yes) 0.804 (0.708–0.900) 0.000 0.620 (0.516–0.725) 0.000 8. Socioeconomic status of household. Quintile 2 Quintile 3 Quintile 4 Quintile 5 Reference – Quintile 1 1 1 -0.241 (-0.380 – -0.103) 0.001 -0.203 (-0.340 – -0.066) 0.004 -0.190 (-0.332–0.049) 0.008 -0.308 (-0.448 – -0.167) 0.000 0.006 (-0.134–0.146) 0.929 -0.178 (-0.318 – -0.039) 0.012 0.527 (0.387–0.667) 0.000 0.152 (0.105–0.294) 0.035 * U_β – Unadjusted beta coefficient; A_β – Adjusted beta coefficient; 95% CI – 95% Confidence Interval. DISCUSSION Aflatoxins are widespread food contaminants in sub-Saharan Africa (SSA), driven by tropical climates, subsistence farming, limited technology, and weak regulation. Despite their serious health risks, alongside the fact that contamination can occur at any point along the food chain and once introduced, often persists throughout, exposure remains largely underreported due to weak surveillance, limited funding, and low policy prioritization(25). In response to the need for stronger community-level evidence on the aflatoxin exposure risks in Africa, this study represents one of the largest population-based aflatoxin KPP surveys conducted in SSA, providing community-level estimates from nearly 18,000 households in a rural coastal farming community. Overall, the level of knowledge about aflatoxin was notably low, with less than half of the population having ever heard of it. This low level of awareness of aflatoxin in foods and its health effects has been previously reported in studies comprising members of African households(26–28). It is reasonable to suggest that a lack of awareness regarding aflatoxin among the study population likely implies the presence of poorly implemented control measures to mitigate contamination and reduce exposure. Indeed, previous surveys among farmers and insights from stakeholders indicate that limited awareness frequently goes hand in hand with poor adoption of aflatoxin control practices(29,30). Our findings revealed limited awareness of foods at risk of aflatoxin contamination, despite widespread consumption of maize, a staple particularly prone to contamination. In this regard, over three-quarters of the study population were reported to consume maize meal three or more times a week, predominantly sourced from local farming and storage practices. This finding aligns with existing research indicating Kenya's exceptionally high maize consumption rates, estimated to stand at 97 kilograms per capita compared to 76 kilograms per capita in East and Southern Africa(31). This concern is heightened by the rising incidence of hepatocellular carcinoma (HCC) in the African region, alongside the higher rates of HCC in rural areas. Although chronic viral hepatitis B infection has traditionally consistently been reported as the most important cause of HCC in Africa and causal attribution cannot be inferred from this study, our findings suggest that aflatoxin may be a hidden yet significant contributor to this trend warranting closer investigation (32–34). Additionally, there was poor awareness of signs and causes of contamination other than discoloration, as well as the health consequences of aflatoxin exposure, with liver cancer being the least identified health outcome. This observation was of interest given the most severe effect of aflatoxin in the human body is seen in the liver, the organ generally responsible for detoxifying chemical agents and poisons(3). Chronic intake of aflatoxin is strongly linked to HCC largely as a result of the genotoxic carcinogenic effects of aflatoxin(35). It is also widely acknowledged that no level of exposure is entirely safe, consequently levels should be minimized wherever possible(35). Notably, maize and sorghum provided in different forms are often used for weaning children in rural Kenyan populations, meaning exposure often begins early in life and continues into adulthood(31). This establishes a pattern of chronic exposure, which is associated with an increased lifetime risk of liver disease. Majority (60.8%) of participants aware of aflatoxin, considered it when purchasing flour, often relying on packaging cues such as the KEBS mark of quality. This finding may partly reflect the Hawthorne effect, with participants potentially reporting greater attention to aflatoxin due to awareness of being surveyed on food safety practices. Of note, over half of study participants suggested using media channels to raise awareness of aflatoxin-safe maize flour, highlighting both consumer interest and the potential channels for effective communication to influence purchasing and production practices. Alternatively, fewer than 30% expressed trust in the safety of Kenyan maize flour brands, indicating a need to address public concerns and explore the reasons behind these doubts. Overall, findings from both complete-case and imputed analyses were consistent, lending support to the assumption that data were missing at random. The higher likelihood of more frequent consumption of maize meal amongst rural populations compared to their peri-urban counterparts is in line with existing observations that point to maize as a staple food in Kenya overall and particularly in rural areas, where it is grown in ninety percent of farms(36). The lower odds of consuming maize meal three or more times per week among households purchasing pre-packed maize, compared with those relying on locally milled maize, further support this pattern. Interestingly high SES households (quintile 4 and 5) were noted to consume maize meal more frequently than their lower SES counterparts, suggesting a sustained preference for ugali even as households move up the wealth ladder, with the key transition being a shift from locally milled to pre-packaged maize meal (37). Similarly, rural households and those of higher-SES were more likely to consider aflatoxin contamination when purchasing food compared to peri-urban and lower-SES households. This occurred despite lower aflatoxin knowledge among rural household heads. A possible explanation is that rural, largely agricultural communities are more directly exposed to the visible consequences of poor farming, storage, and handling practices, such as mouldy grains. This lived experience may encourage caution when buying maize meal, even if technical knowledge is limited. Supporting this, a study in Western Kenya found that while only 20% of rural caregivers had heard of aflatoxins, over 60% recognized visual spoilage indicators (e.g., mould, dampness) and linked them to crop spoilage and potential causes(38). Additionally, individuals who had ever attended school as well as those of higher SES (quintile 5) also appeared to consider aflatoxin contamination more commonly than their counterparts, a fact likely influenced by a greater awareness and purchasing power, enabling them to prioritize food safety(39). Interestingly, although women play a significant role in agricultural and post-harvest activities, including food preparation(40), female household heads demonstrated lower levels of aflatoxin-related knowledge than their male counterparts. Similar findings have been reported in studies from other SSA countries, including Nigeria and other areas of Kenya, suggesting a broader regional pattern(26,41). The observed association, where aflatoxin-related knowledge increased with higher SES and school attendance but was lower among rural and female household heads, may reflect disparities in access to education, information, and resources, such as agricultural extension services. It is important to acknowledge that this study is not without its limitations. Firstly, we must acknowledge the potential for social desirability bias. The exclusive use of quantitative methods also limited in-depth understanding of participants’ perceptions, such as concerns about Kenyan maize flour, and agricultural practices which are central to aflatoxin risk. Though the latter was not explored in this study, complementary data from a subsample of smallholder farmers offers additional insights (18). Despite these limitations, the study has strengths that enhance its credibility, including a census-based sampling approach with a high response rate and engagement of respected CHPs, enabling contextual understanding. Aflatoxin remains a critical global food safety concern, disproportionately affecting rural subsistence farming communities in LMICs. Our findings emphasize the need to raise aflatoxin awareness in rural farming populations, particularly among women, potentially by engaging agricultural extension workers or civil society and community-based organizations to strengthen literacy, promote safe food handling practices, and ultimately reduce exposure. Importantly, limited dietary diversity (potentially driven by food insecurity) further increases vulnerability to aflatoxin exposure and its associated health effects. This reality is highly relevant to our study population, where nearly 70% live below the poverty line. Taken together, these findings emphasize the need for multifaceted interventions that raise awareness, improve food handling practices, and address underlying food security challenges as well as dietary behaviour, providing a roadmap for reducing aflatoxin exposure and its health impacts in vulnerable rural communities. Abbreviations Adjusted beta coefficient A_β Adjusted odds ratio A_OR Aspergillus flavus A. flavus Aspergillus parasiticus A. parasiticus Comma Separated Values–CSV Community Health Promoters CHPs Complete case analysis–CCA Demographic and Health Surveillance DHS Hepatocellular carcinoma HCC Kaloleni Rabai Health and Demographic Surveillance System KRHDSS Kenya Bureau of Standards KEBS Knowledge Perception Practice KPP Low and–middle–income countries–LMICs Multiple imputation MI National Commission for Science, Technology and Innovation NACOSTI Socioeconomic status SES Standard deviation SD sub Saharan Africa–SSA Unadjusted beta coefficient U_β Unadjusted odds ratio U_OR 95% Confidence Interval 95% CI Declarations ETHICS APPROVAL AND CONSENT TO PARTICIPATE The study was approved by the Aga Khan University Institutional Scientific and Ethical Review Committee (AKU-ISERC) (2013/IREC-65(v10)) and undertaken in accordance with the Declaration of Helsinki. CONSENT FOR PUBLICATION Written informed consent was obtained from all study participants, including consent to publish study findings. AVAILABILITY OF DATA AND MATERIALS Any interested parties can apply directly to the corresponding author to access the data used in this paper by contacting them at [email protected] COMPETING INTERESTS The Authors declare that there is no ‘conflict of interest’. FUNDING This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. This work was supported through internal university funding made available by the Aga Khan University (AKU) Department of Haematology and Oncology (DHO) and Kaloleni-Rabai Health and Demographic Surveillance System (KRHDSS). AUTHOR CONTRIBUTIONS "RIO provided input in the design of this study protocol, oversaw the implementation of this study and was responsible for analysis of data as well as finding relevant literature and leading drafting of this manuscript." "JA provided input in the review and editing of the manuscript." "AN provided input in the design of this study protocol, implementation of the study protocol and drafting of this manuscript." “IA provided input in the design of this study protocol, participated in development of the data collection tool, implementation of this study as well as review and editing of the manuscript.” "MS led acquisition of funding for this study as well as participated in development of the study protocol and data collection tool as well as review and editing of the manuscript.” "All authors read and approved the final manuscript." ACKNOWLEDGMENTS We gratefully acknowledge the support from Kaloleni-Rabai leadership, as well as the participating Community Health Units, and their teams of Community Health Promoters. References Shabeer S, Asad S, Jamal A, Ali A. Aflatoxin Contamination, Its Impact and Management Strategies: An Updated Review. 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Socioeconomic Characteristics Influencing Level of Awareness of Aflatoxin Contamination of Feeds among Livestock Farmers in Meru District of Tanzania. 2018 Apr 30 [cited 2025 Oct 22]; Available from: https://dspace.nm-aist.ac.tz/handle/20.500.12479/1081 Onyalo PO. WOMEN AND AGRICULTURE IN RURAL KENYA: ROLE IN AGRICULTURAL PRODUCTION. 2019;4. Cheruiyot C, Okoth MW, Abong’ GO, Kariuki SW. Knowledge, Attitudes, and Food Safety Practices of Informal Market Maize Grain Vendors and Consumers in Meru County, Kenya. Int J Food Sci [Internet]. 2024 Nov 21 [cited 2025 Oct 22];2024:6592430. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC11606682/ APPENDICES APPENDIX 1 : Exploration of Missing Data Patterns Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile1DataCollectionToolEnglishVersion.docx APPENDICES.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 17 Mar, 2026 Reviews received at journal 14 Mar, 2026 Reviewers agreed at journal 11 Mar, 2026 Reviews received at journal 10 Mar, 2026 Reviewers agreed at journal 10 Mar, 2026 Reviews received at journal 09 Mar, 2026 Reviewers agreed at journal 16 Feb, 2026 Reviewers agreed at journal 14 Feb, 2026 Reviewers invited by journal 12 Feb, 2026 Editor assigned by journal 12 Feb, 2026 Editor invited by journal 09 Feb, 2026 Submission checks completed at journal 06 Feb, 2026 First submitted to journal 06 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8785894","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":592794640,"identity":"07deb4c0-d9ab-413b-a269-c279cc8fb343","order_by":0,"name":"Rosebella Iseme-Ondiek","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIie3RsWrDMBCA4QsGdzmT9YLT9BVkBGogps/iEpCWDh4zZBAU7NFrhjyMwKAseoCMDYVmyVDo2JLWNKWlgxW6ddA/iUMfHBxAKPRPiwCm488XMmBDiL+GfkL4TUb6bwSAMXOGXNf17rFcEA51ZB8OZc75xkqCxexW95Cxc5yvHCGZWGVrJoVw0hI41UuI7uI0qbrFDIoUWZsLoyoaVK2HqP1rciS8OpH3nDf7jhx9pBBRognZiRjBqFtsoD0EHU9XljBrYzlaszmn7dN8WljFe8lFvXspl/lksrm3dHi7yZpGZtvn5eyyj/z06xDF2e+hUCgU8vUB0IpM7w/yMJsAAAAASUVORK5CYII=","orcid":"","institution":"Aga Khan University Nairobi","correspondingAuthor":true,"prefix":"","firstName":"Rosebella","middleName":"","lastName":"Iseme-Ondiek","suffix":""},{"id":592794641,"identity":"df40a2b0-e07f-4974-a322-128bc3d998f1","order_by":1,"name":"Joseph Abuodha","email":"","orcid":"","institution":"Aga Khan University","correspondingAuthor":false,"prefix":"","firstName":"Joseph","middleName":"","lastName":"Abuodha","suffix":""},{"id":592794642,"identity":"30235f0f-80b7-489b-a050-01f9fd672e7e","order_by":2,"name":"Anthony Ngugi","email":"","orcid":"","institution":"Aga Khan University Nairobi","correspondingAuthor":false,"prefix":"","firstName":"Anthony","middleName":"","lastName":"Ngugi","suffix":""},{"id":592794643,"identity":"5752f0eb-68c5-4335-92b6-e38141d1507c","order_by":3,"name":"Innocent Abayo","email":"","orcid":"","institution":"IQVIA","correspondingAuthor":false,"prefix":"","firstName":"Innocent","middleName":"","lastName":"Abayo","suffix":""},{"id":592794644,"identity":"909e0aa8-a57b-4e5e-aca3-52b91b654ca2","order_by":4,"name":"Mansoor Saleh","email":"","orcid":"","institution":"Aga Khan University","correspondingAuthor":false,"prefix":"","firstName":"Mansoor","middleName":"","lastName":"Saleh","suffix":""}],"badges":[],"createdAt":"2026-02-04 11:38:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8785894/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8785894/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102985666,"identity":"e9b8a7a6-02c6-420f-a19b-005a7103247e","added_by":"auto","created_at":"2026-02-19 10:12:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1683972,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8785894/v1/c4d022c4-2322-4371-b2b9-833233762b64.pdf"},{"id":102985510,"identity":"e55dbf89-b147-4fae-8b85-3f6921d1ecc8","added_by":"auto","created_at":"2026-02-19 10:11:32","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":27625,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1DataCollectionToolEnglishVersion.docx","url":"https://assets-eu.researchsquare.com/files/rs-8785894/v1/09ed07376aa1b2c18dd38616.docx"},{"id":102985523,"identity":"40ff9473-a6d7-4e00-b120-3c94042742f6","added_by":"auto","created_at":"2026-02-19 10:11:40","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":40382,"visible":true,"origin":"","legend":"","description":"","filename":"APPENDICES.docx","url":"https://assets-eu.researchsquare.com/files/rs-8785894/v1/105c9a205299ec0f1166d81a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessing Aflatoxin Knowledge, Perceptions, and related Practices, in a Rural Coastal Community: A Population-Based Cross-sectional Survey","fulltext":[{"header":"KEY MESSAGE","content":"\u003cp\u003e\u003cstrong\u003eWhat is already known about this topic?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAflatoxin contamination is a major yet under-addressed food safety challenge in low-resource settings. \u0026nbsp;In the absence of analytical methods for community-level detection of aflatoxin exposure, low-cost household surveillance approaches capable of estimating exposure risks at the community level can be highly informative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat does this study add?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe limited awareness of aflatoxin in our study population (particularly among rural residents, poorer households, and individuals without formal education) suggests the presence of poorly implemented control measures to mitigate contamination and reduce exposure.\u003c/p\u003e\n\u003cp\u003eMaize is consumed frequently establishing a pathway for chronic aflatoxin exposure. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHow might these findings affect research, practice, or policy?\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThese findings signal an urgent need to prioritize aflatoxin prevention by investing in surveillance and embedding community education into agricultural and health programs.\u003c/p\u003e"},{"header":"BACKGROUND","content":"\u003cp\u003eAflatoxins are naturally occurring toxins produced by certain fungi, most importantly Aspergillus flavus (\u003cem\u003eA. flavus\u003c/em\u003e) and Aspergillus parasiticus (\u003cem\u003eA. parasiticus\u003c/em\u003e)(1). Aflatoxins contaminate many African dietary staples such as maize and maize products, groundnuts and its produce as well as other legumes and oilseeds, rice, cassava, sorghum, millet, and yams (1,2). They have also been reported in herbal products(2). Contamination occurs under certain conditions, namely, dry weather near crop maturity, high moisture during harvest, and inadequate drying and storage of crops(1). If aflatoxin-contaminated crops are consumed by humans, aflatoxin poisoning (i.e. aflatoxicosis) can occur. Acute aflatoxin toxicity may result in nausea, vomiting, abdominal pain, convulsions, and other signs of acute liver injury(3). Importantly, chronic exposure to even low levels of contamination in crops consumed regularly increases the risk of liver cancer and can suppress the immune system(4). Exposure to high levels of aflatoxin can be fatal(4).\u003c/p\u003e \u003cp\u003eAflatoxins can also enter the human diet through livestock products if the livestock are given contaminated feed(5). Consequently, exposure can also occur through consumption of animal products such as blood, eggs, ghee, meat, milk, and dairy products. Children can also be affected through breast milk or direct consumption of weaning foods, extending the risk of negative health impacts to very young populations(6,7). Exposure to aflatoxins can also occur through dust inhalation during processing of contaminated crops and feeds(8). The toxins can also permeate the skin as well as cause foetal exposure in-utero (aflatoxin is known to cross the placenta)(8,9). Existing literature also suggests an association between aflatoxin exposure and child growth stunting(10). As such, aflatoxin constitutes a significant public health concern.\u003c/p\u003e \u003cp\u003eTypically, many rural African communities, rely heavily on agriculture, employing about 70% of their populations(11). The reliance on semi-subsistence farming, devoid of centralized food systems, leaves inhabitants vulnerable to aflatoxin exposure due to inadequate infrastructure for monitoring food and feed safety(2). This risk is further exacerbated by the lack of irrigation, as well as improper drying and storage facilities(12). Notably, the prevalence of aflatoxin contamination is increasing across Africa, driven in part by the growing impacts of climate change(13). Importantly, cereals and legumes vulnerable to aflatoxin contamination, which serve as dietary staples in many rural households, are also commonly used in weaning and complementary feeding for infants and young children(2). This unique blend of environmental and socioeconomic factors significantly heightens the risk of aflatoxin contamination and subsequent exposure among the region\u0026rsquo;s population, beginning early in life.\u003c/p\u003e \u003cp\u003eIn Kenya, aflatoxins are widely recognized as a persistent problem(14). However, a nationally representative cross-sectional serosurvey which analysed serum specimens for aflatoxin levels, revealed marked regional variations in exposure(15). In this study, the Coast region ranked second highest, highlighting the urgent need for targeted studies whose findings may guide interventions in this high-risk area. \u003cem\u003eA. flavus\u003c/em\u003e, is considered the primary producer of aflatoxins affecting Kenya\u0026rsquo;s agricultural commodities, and it thrives in conditions mirroring those found in Kilifi County, one of the nation's five coastal counties(14). Kilifi County is characterised by an erratic tropical climate comprising periodic droughts, high humidity, and high temperatures, conducive to \u003cem\u003eA. flavus\u003c/em\u003e growth(16). Kilifi County also grapples with socioeconomic challenges, including high poverty rates (71% rate of absolute poverty compared to the national average of 47%) and low education levels, alongside a population predominantly composed of smallholder farmers where over 50% of the county\u0026rsquo;s inhabitants derive their livelihoods from crop and livestock production(16,17). In addition, maize, cowpea, cassava, and nuts (all aflatoxin susceptible crops) are amongst the key staples grown and consumed in the County(18).\u003c/p\u003e \u003cp\u003eSince aflatoxin contamination cannot be visually detected without specialized tools, Knowledge, Perceptions, and Practice (KPP) surveys provide a cost-effective means of assessing population-level exposure risks in resource-limited settings. In the absence of affordable community-level analytical methods, household surveys yield valuable insights to guide targeted mitigation measures. We therefore conducted a population-based survey among household heads in a predominantly agricultural rural coastal community to evaluate knowledge, perceptions, and practices related to aflatoxin. Specifically, the survey assessed whether vulnerable farming households recognize foods prone to contamination, understand the causes and signs of aflatoxin, and are aware of prevention strategies. This is critical, as evidence consistently shows that populations with stronger awareness of health risks and preventive measures are more likely to adopt protective practices(19,20). The findings will inform the development of interventions to mitigate aflatoxin exposure in Kilifi as well as other similarly affected settings.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and objectives\u003c/h2\u003e \u003cp\u003eA cross-sectional population-based survey (nested in an existing surveillance platform) was utilized to assess the knowledge, perceptions and practices pertaining to aflatoxin contamination, associated health risks and prevention amongst household heads of a rural coastal community. Data were collected between July and December 2022.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy setting, study participants and sampling\u003c/h3\u003e\n\u003cp\u003eThe study was undertaken in the largely rural areas of southern Kilifi, one of five coastal counties in Kenya. The Department of Population Health at Aga Khan University in collaboration with the local health department operates a health and demographic surveillance system, that tracks approximately 103,000 inhabitants of two sub-counties (Kaloleni and Rabai) within this area. This ongoing endeavour employs the use of distinct identifiers that enables longitudinal monitoring of all individuals enumerated within the surveillance platform. The study area, its population, and the surveillance platform have been comprehensively described in previous publications(21,22). Of note, roughly 70% of the populace resides below the poverty threshold, with 81% dependent on subsistence agriculture, crafts, sporadic employment, and small-scale trading to sustain their livelihoods(21).\u003c/p\u003e \u003cp\u003eThe target population for this survey were household heads of all households that form part of the Kaloleni Rabai Health and Demographic Surveillance System (KRHDSS). A census approach (targeting 100% inclusion of all household heads) was used, with all household heads invited to participate in the study through household visits by trained community health promoters (CHPs). The CHPs serve as a cohesive network of community resource personnel responsible for gathering surveillance data and providing household-level health education and health promotion(23). Therefore, they were well-positioned to conduct the aflatoxin survey during routine surveillance data collection. A total of 20,502 household heads were targeted for inclusion in this study.\u003c/p\u003e\n\u003ch3\u003eData collection tools and approaches\u003c/h3\u003e\n\u003cp\u003eData were collected by trained CHPs using face-to-face electronic interviewer administered questionnaires. The latter underwent training over a week-long period, which encompassed role-playing scenarios as well as piloting the data collection tools in the field before commencing the actual data collection. After the role-play and piloting exercises, necessary modifications and correction took place to ensure reliability and validity of the data collection tool.\u003c/p\u003e \u003cp\u003eThe semi-structured questionnaires were originally designed in paper form and thereafter digitized and deployed on electronic data collection tablets. Electronic data capture enabled direct uploads from the field to a web-based database and real-time checking for data quality.\u003c/p\u003e \u003cp\u003eThe data collection tool included inquiries regarding sociodemographic traits of household heads (such as age, sex, education, and occupation), medical history, assets owned and frequency of consuming foods susceptible to aflatoxin contamination. It also delved into the origins of such foods, awareness levels concerning aflatoxin, knowledge regarding signs and causes of contamination, transmission modes, and health repercussions. Additionally, it explored perceptions toward its significance and strategies employed to safeguard households from exposure. The full questionnaire is available in \u003cb\u003eSupplementary File 1.\u003c/b\u003e\u003c/p\u003e\n\u003ch3\u003eData management and analysis\u003c/h3\u003e\n\u003cp\u003eQuantitative data analysis was undertaken using STATA version 13 (StataCorp. 2013)(24). Data in Comma-Separated Values (CSV) format was extracted from the database and directly imported into STATA. Duplicate entries were erased, and any erroneous responses and missing data identified and rectified through a re-survey of the household head. The variables of interest were either continuous or categorical measures. Descriptive statistics, including means, standard deviations (SD), frequencies, and percentages, were employed to elucidate the distribution of knowledge, perceptions, and practices within our study cohort.\u003c/p\u003e \u003cp\u003eAflatoxin knowledge was operationalized as a composite score derived from responses to six domains, i.e., foods at risk, signs and modes of contamination, causes of contamination, control measures and health effects of aflatoxin exposure. Correct responses were summed to generate a continuous knowledge score (range 0\u0026ndash;19).\u003c/p\u003e \u003cp\u003ePrincipal component analysis was carried out to develop a five-point asset-based socioeconomic status (wealth index) scale using the Demographic and Health Surveillance (DHS) Wealth Index approach and data generated from the household-based interviews with household heads. The first principal component was used to define the asset index. Households were divided into five wealth quintiles (from poorest to wealthiest) based on the composite wealth index score. DHS wealth quintiles are widely used across several health areas for examining health outcomes by wealth status in low- and middle- income countries (LMICs) to understand patterns of service utilisation, inequalities and disparities. Regression (linear and logistic as appropriate) was carried out to find the contribution of predefined independent variables to household head knowledge, perceptions and practices related to aflatoxin as appropriate.\u003c/p\u003e \u003cp\u003eIn order to address missing socio-economic status (SES) data, analyses were conducted using both complete-case analysis (CCA) and multiple imputation (MI). CCA included only participants with complete information for all variables, while MI used chained equations to generate 20 imputed datasets under the assumption of data missing at random. The latter assumption meant that the probability of missingness was related to observed variables in the dataset but not to the unobserved values themselves. This assumption was considered reasonable in this study because patterns of missingness were plausibly explained by measured participant characteristics (, i.e., age, sex, place of residence, school attendance, level of knowledge of aflatoxin, frequency of consumption of maize meal, and consideration of aflatoxin when making food purchases) as evidenced by the findings of bivariate analyses (\u003cb\u003eAppendix 1\u003c/b\u003e). A single analysis model was applied across all imputed datasets, with estimates pooled using Rubin\u0026rsquo;s rules to incorporate both within- and between-imputation variability. Results from both approaches (CCA and MI) were compared to assess the potential impact of missing data on effect estimates and statistical significance (set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n\u003ch3\u003eEthical considerations\u003c/h3\u003e\n\u003cp\u003e The proposal obtained clearance from the Institutional Scientific and Ethics Review Committee at Aga Khan University (Approval No: 2013/REC-65(version10)). Furthermore, a research permit was granted by the National Commission for Science, Technology, and Innovation (License No: NACOSTI/P/22/18630). Subsequently, necessary approvals were obtained from the county offices, and informed consent was acquired from each study participant. Various measures were implemented to ensure the privacy and confidentiality of respondents including the use of unique anonymous identifiers, and limiting data access to authorised persons only, which was safeguarded by password protection.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe aflatoxin household survey recorded an 86.9% (n\u0026thinsp;=\u0026thinsp;17,813) response rate which is well above the 80% acceptable minimum threshold set for household surveys. Reasons for non-participation were not recorded. Out of the 17, 813 household heads who were surveyed, three-quarter were males (n\u0026thinsp;=\u0026thinsp;13,342; 74.9%). In addition, amongst the 11,525 (64.7%) household heads who had received some form of formal education, the majority (n\u0026thinsp;=\u0026thinsp;8,582; 74.5%) stated that primary school education was their highest level of academic achievement. Furthermore, more males than females had ever received any formal education, i.e., 75.2% versus 33.3% respectively. The mean age of household heads was approximately 49.1 (SD\u0026thinsp;=\u0026thinsp;16.1) years, with female household heads being older (mean\u0026thinsp;=\u0026thinsp;54.4 years, SD\u0026thinsp;=\u0026thinsp;16.5 years) than male household heads (mean\u0026thinsp;=\u0026thinsp;47.3, SD\u0026thinsp;=\u0026thinsp;15.6 years). Additionally, the most common occupation amongst this study sample was farming (n\u0026thinsp;=\u0026thinsp;5,757; 32.3%). Importantly, less than half of the study sample reported any hospital visit in the 12 months preceding the survey, regardless of whether the visit was for routine care, treatment, or screening (n\u0026thinsp;=\u0026thinsp;8,223; 46.2%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of study respondents.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFemales\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;4,471 (25.1%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMales\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;13,342 (74.9%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;17,813 (100.0%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.37 (16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.29 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.07 (16.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormal Education (Yes), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,489 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10,036 (75.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11,525 (64.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e3.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHighest level of education attained.\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;11,525), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrimary \u0026ndash;\u003c/p\u003e \u003cp\u003e1,175 (78.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimary \u0026ndash;\u003c/p\u003e \u003cp\u003e7,407 (73.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrimary \u0026ndash;\u003c/p\u003e \u003cp\u003e8,582 (74.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecondary \u0026ndash;\u003c/p\u003e \u003cp\u003e271 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSecondary \u0026ndash; 2,344 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSecondary \u0026ndash;\u003c/p\u003e \u003cp\u003e2,615 (22.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTertiary \u0026ndash;\u003c/p\u003e \u003cp\u003e43 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTertiary \u0026ndash;\u003c/p\u003e \u003cp\u003e285 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTertiary \u0026ndash;\u003c/p\u003e \u003cp\u003e328 (2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003e4.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eOccupation, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEmployed worker \u0026ndash; 197 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEmployed worker \u0026ndash; 2,960 (22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEmployed worker \u0026ndash; 3,157 (17.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCasual worker \u0026ndash; 395 (8.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCasual worker \u0026ndash; 4,493 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCasual worker \u0026ndash; 4,888 (27.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrader \u0026ndash;\u003c/p\u003e \u003cp\u003e469 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTrader \u0026ndash;\u003c/p\u003e \u003cp\u003e1,316 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTrader \u0026ndash;\u003c/p\u003e \u003cp\u003e1,785 (10.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFarmer \u0026ndash;\u003c/p\u003e \u003cp\u003e2,139 (47.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFarmer \u0026ndash;\u003c/p\u003e \u003cp\u003e3,618 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFarmer \u0026ndash;\u003c/p\u003e \u003cp\u003e5,757 (32.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHousewife \u0026ndash;\u003c/p\u003e \u003cp\u003e1,149 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHousewife \u0026ndash;\u003c/p\u003e \u003cp\u003e1,149 (6.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOther \u0026ndash; 122 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOther \u0026ndash; 955 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOther \u0026ndash; 1,077 (6.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion that visited a hospital in the 12 months preceding the survey for routine care, treatment, or screening, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,442 (54.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,781 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,223 (46.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion that had blood work done in the 12 months preceding the survey, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e742 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,621 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,363 (13.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWealth quintiles, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eQuintile 1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,137 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,249 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,386 (19.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eQuintile 2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e974 (21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,460 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,434 (19.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eQuintile 3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e718 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,451 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,169 (17.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eQuintile 4\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e688 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,610 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,298 (18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eQuintile 5\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e595 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,742 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,337 (18.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMissing\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e359 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e830 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,189 (6.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOverall, the level of awareness and knowledge of aflatoxin amongst this study sample was considerably low. Only half, i.e., 49.5% (95%CI: 48.8% \u0026minus;\u0026thinsp;50.2%) of the study population stated that they had ever heard of aflatoxin and subsequent interview questions were administered only to these. Only a few were able to identify foods that were contaminated by aflatoxin (n\u0026thinsp;=\u0026thinsp;1,657; 18.8%), the signs of aflatoxin contamination (n\u0026thinsp;=\u0026thinsp;1,526; 17.3%), the causes of aflatoxin contamination (n\u0026thinsp;=\u0026thinsp;829; 9.4%) and the health effects associated with exposure to this toxin (none of the respondents correctly identified the complete set of listed health effects associated with aflatoxin exposure). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e outlines the results from the knowledge assessments.\u003c/p\u003e \u003cp\u003eMaize (n\u0026thinsp;=\u0026thinsp;7,318; 83.0%) and wheat (n\u0026thinsp;=\u0026thinsp;4,270; 48.4%) emerged as the most correctly recognized foods susceptible to aflatoxin contamination, with discoloration (n\u0026thinsp;=\u0026thinsp;6,330; 71.8%) being the widely acknowledged sign of such contamination. In contrast, participants showed least awareness of a mouldy smell as an indication of aflatoxin presence, and drying maize on the ground was the least recognized cause of maize contamination with aflatoxin. The commonly known causes of contamination were poorly dried or wet maize (n\u0026thinsp;=\u0026thinsp;6,445; 73.2%) and inadequate storage practices (n\u0026thinsp;=\u0026thinsp;5,575; 63.2%). Moreover, liver cancer (n\u0026thinsp;=\u0026thinsp;547; 6.2%) was the least identified health consequence of aflatoxin exposure, with respondents more commonly associating exposure with stunted growth in children (n\u0026thinsp;=\u0026thinsp;2,751; 31.2%) and immune suppression (n\u0026thinsp;=\u0026thinsp;1,874; 21.3%).\u003c/p\u003e \u003cp\u003eAflatoxin-related knowledge scores ranged from 1 to 19. The scores were approximately normally distributed, with a mean of 6.2 (SD\u0026thinsp;=\u0026thinsp;3.1) and a median of 6 (Interquartile range: 3\u0026ndash;8), indicating that 50% of participants scored below 6. For a detailed breakdown of responses to the knowledge questions, and the scoring methodology refer to \u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003e\u003cb\u003eAppendix 2\u003c/b\u003e\u003c/span\u003e\u003cb\u003ea and b\u003c/b\u003e, respectively.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKnowledge of Aflatoxin (n\u0026thinsp;=\u0026thinsp;17,813)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKnowledge questions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal - n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale - n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMale - n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAware of aflatoxin.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,816 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,955 (43.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,861 (51.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e2.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKnowledge of foods contaminated by aflatoxin*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaize, Wheat, and Milk \u0026ndash; 1,657 (18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMaize, Wheat, and Milk \u0026ndash; 384 (19.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMaize, Wheat, and Milk \u0026ndash; 1,273 (18.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 1,437 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 233 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 1,204 (17.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e3.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKnowledge of signs of aflatoxin contamination in maize*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDiscolouration, Mouldiness and wetness, Presence of insects and Mouldy smell \u0026ndash; 1,526 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiscolouration, Mouldiness and wetness, Presence of insects and Mouldy smell \u0026ndash; 359 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDiscolouration, Mouldiness and wetness, Presence of insects and Mouldy smell \u0026ndash; 1,167 (17.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 876 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 167 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 709 (10.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e4.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKnowledge of causes of contamination of maize with aflatoxin*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoorly dried or wet maize, Poor storage of maize, Drying maize on the ground, Shelling wet maize \u0026ndash; 829 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoorly dried or wet maize, Poor storage of maize, Drying maize on the ground, Shelling wet maize \u0026ndash; 168 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePoorly dried or wet maize, Poor storage of maize, Drying maize on the ground, Shelling wet maize \u0026ndash; 661 (9.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 219 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 62 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 157 (2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e5.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eKnowledge of health effects of aflatoxin exposure*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStunting in children, Immunity suppression, Liver cirrhosis, Death \u0026ndash; 0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStunting in children, Immunity suppression, Liver cirrhosis, Death \u0026ndash; 0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStunting in children, Immunity suppression, Liver cirrhosis, Death \u0026ndash; 0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 1,325 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 412 (21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eI don\u0026rsquo;t know \u0026ndash; 913 (13.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAflatoxin can be transmitted through breast milk and contaminated chicken meat. * (Yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,614 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e345 (17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,269 (18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAflatoxin can be destroyed through processes like cooking, boiling, and baking. * (No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,843 (43.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e855 (43.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,988 (43.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Responses to knowledge questions are only among those who stated they were aware of aflatoxin. Results are presented for respondents who identified all correct answers and for those who explicitly stated they did not know the correct answer. See \u003cspan refid=\"Sec12\" class=\"InternalRef\"\u003eappendix 2\u003c/span\u003e for detailed breakdown of responses to the knowledge questions.\u003c/p\u003e \u003cp\u003e Only participants that were aware of aflatoxin were asked to answer questions regarding their perceptions of this contaminant. The results showed that more than half (n\u0026thinsp;=\u0026thinsp;5,353; 60.8%) of participants who were aware of aflatoxin, considered it when making flour purchases. Amongst respondents who did consider aflatoxin when purchasing flour, the communication on the packaging was the frequently reported strategy (n\u0026thinsp;=\u0026thinsp;2,633; 49.1%) used to determine whether flour was \u0026lsquo;aflatoxin safe\u0026rsquo;. In this regard, participants relied on the presence of the Kenya Bureau of Standards (KEBS) mark of quality as the sought after indicator of safety. Interestingly, almost a third (n\u0026thinsp;=\u0026thinsp;2,574; 29.2%) of the respondents believed there were Kenyan maize brands that were considered aflatoxin safe. When all study respondents (irrespective of awareness of aflatoxin) were asked what could be done to create more awareness around aflatoxin safe maize flour, a greater portion of study respondents (n\u0026thinsp;=\u0026thinsp;9,128; 51.2%) stated communication (either through Radio, Television and Billboards) should be undertaken. Regarding aflatoxin-related practices, most respondents (n\u0026thinsp;=\u0026thinsp;13,818; 77.6%) consumed maize meal three or more times a week. Similarly, most respondents (n\u0026thinsp;=\u0026thinsp;12,346; 69.3%) consumed maize meal that is locally farmed and stored (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003ePerceptions and Practices related to Aflatoxin.\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerception Statements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemales - n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMales \u0026ndash; n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal - n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e*Proportion that considers aflatoxin while purchasing maize flour.\u003c/p\u003e \u003cp\u003e\u003cb\u003e(females\u0026thinsp;=\u0026thinsp;1,955; males\u0026thinsp;=\u0026thinsp;6,861)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,159\u003c/p\u003e \u003cp\u003e(59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,204\u003c/p\u003e \u003cp\u003e(61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5,363\u003c/p\u003e \u003cp\u003e(60.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e⁺Strategies used to determine flour is aflatoxin safe. \u003cb\u003e(females\u0026thinsp;=\u0026thinsp;1,159; males\u0026thinsp;=\u0026thinsp;4,204)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e⁺Rely on word of mouth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e330\u003c/p\u003e \u003cp\u003e(28.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,322\u003c/p\u003e \u003cp\u003e(31.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,652\u003c/p\u003e \u003cp\u003e(30.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e⁺Communication on package\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e586\u003c/p\u003e \u003cp\u003e(50.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,047\u003c/p\u003e \u003cp\u003e(48.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,633\u003c/p\u003e \u003cp\u003e(49.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e⁺Communication from media outlets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e243\u003c/p\u003e \u003cp\u003e(21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e835 (19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,078\u003c/p\u003e \u003cp\u003e(20.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e*Proportion that believes there are Kenyan maize brands that are aflatoxin safe.\u003c/p\u003e \u003cp\u003e\u003cb\u003e(females\u0026thinsp;=\u0026thinsp;1,955; males\u0026thinsp;=\u0026thinsp;6,861)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e546\u003c/p\u003e \u003cp\u003e(27.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,028\u003c/p\u003e \u003cp\u003e(29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,574\u003c/p\u003e \u003cp\u003e(29.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eMeasures that should be taken to create more awareness around aflatoxin safe maize flour.\u003c/p\u003e \u003cp\u003e\u003cb\u003e(females\u0026thinsp;=\u0026thinsp;4,472; males\u0026thinsp;=\u0026thinsp;13,342)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdvocacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e618\u003c/p\u003e \u003cp\u003e(13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1525\u003c/p\u003e \u003cp\u003e(11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2143\u003c/p\u003e \u003cp\u003e(12.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunication- Radio, Television, Billboards\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2145\u003c/p\u003e \u003cp\u003e(48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6983\u003c/p\u003e \u003cp\u003e(52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9128\u003c/p\u003e \u003cp\u003e(51.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndorsement by medical experts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1388\u003c/p\u003e \u003cp\u003e(31.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4245\u003c/p\u003e \u003cp\u003e(31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5633\u003c/p\u003e \u003cp\u003e(31.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e320\u003c/p\u003e \u003cp\u003e(7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e587\u003c/p\u003e \u003cp\u003e(4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e907\u003c/p\u003e \u003cp\u003e(5.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eAflatoxin related practices \u003cb\u003e(females\u0026thinsp;=\u0026thinsp;4,471; males\u0026thinsp;=\u0026thinsp;13,342)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProportion of household heads consuming ugali (maize meal) \u0026ge;3X/Week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,475\u003c/p\u003e \u003cp\u003e(77.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,343\u003c/p\u003e \u003cp\u003e(77.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13,818\u003c/p\u003e \u003cp\u003e(77.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProportion of household heads that consume maize meal that is locally farmed and stored.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,876\u003c/p\u003e \u003cp\u003e(64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,470\u003c/p\u003e \u003cp\u003e(71.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12,346\u003c/p\u003e \u003cp\u003e(69.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProportion of household heads that consume maize meal that is pre-packed.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,486\u003c/p\u003e \u003cp\u003e(78.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10,826\u003c/p\u003e \u003cp\u003e(81.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14,312\u003c/p\u003e \u003cp\u003e(80.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Responses to questions on whether they consider aflatoxin while purchasing maize flour and whether there are available Kenyan maize brands that are aflatoxin safe are only among those who stated they were aware of aflatoxin (n\u0026thinsp;=\u0026thinsp;8,816). ⁺The question regarding how respondents determine aflatoxin is safe was answered ONLY by respondents who stated they considered aflatoxin when purchasing flour. ⁺ Respondents answering this question were able to pick multiple responses. All 17,813 respondents answered the question regarding what could be done to create more awareness as well as aflatoxin practice related questions.\u003c/p\u003e \u003cp\u003eA total of 6.7% (n\u0026thinsp;=\u0026thinsp;1,189) of households had missing household asset data and, consequently, no assigned wealth quintile (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A comparison of results from the complete case analysis - CCA (\u003cb\u003eAppendix 3\u003c/b\u003e) and the estimates generated using the imputed data (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) yielded similar findings. Rural residency \u003cb\u003e(Imputed findings -\u003c/b\u003e A_OR\u0026thinsp;=\u0026thinsp;1.9, 95% CI: 1.8\u0026ndash;2.1\u003cb\u003e)\u003c/b\u003e, and higher SES \u003cb\u003e(Imputed findings Quintile 4 -\u003c/b\u003e A_OR\u0026thinsp;=\u0026thinsp;1.1, 95% CI: 1.0\u0026ndash;1.3; \u003cb\u003eImputed findings Quintile 5 -\u003c/b\u003e A_OR\u0026thinsp;=\u0026thinsp;1.3, 95% CI: 1.2\u0026ndash;1.5\u003cb\u003e)\u003c/b\u003e, were significantly associated with increased odds of consuming maize meal three or more times per week, whilst consumption of pre-packed maize meal (when compared with maize meal that is locally milled) showed a modest reduced odds (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and \u003cb\u003eAppendix 3a\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eSimilarly, rural residency \u003cb\u003e(Imputed findings -\u003c/b\u003eA_OR\u0026thinsp;=\u0026thinsp;1.1, 95% CI: 1.1\u0026ndash;1.2\u003cb\u003e)\u003c/b\u003e, school attendance \u003cb\u003e(Imputed findings -\u003c/b\u003eA_OR\u0026thinsp;=\u0026thinsp;1.4, 95% CI: 1.3\u0026ndash;1.5\u003cb\u003e)\u003c/b\u003e, and higher SES \u003cb\u003e(Imputed findings Quintile 5 -\u003c/b\u003e A_OR\u0026thinsp;=\u0026thinsp;1.1, 95% CI: 1.0\u0026ndash;1.3\u003cb\u003e)\u003c/b\u003e were positively associated with considering aflatoxin when making household food purchases. In addition, greater aflatoxin-related knowledge was also found to increase the odds of considering aflatoxin during household food purchase decisions as well as consuming maize meal three or more times per week, across both analyses (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb and \u003cb\u003eAppendix 3b\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eNotably, aflatoxin-related knowledge was higher among those who had ever attended school \u003cb\u003e(Imputed findings -\u003c/b\u003e A_β\u0026thinsp;=\u0026thinsp;0.6, 95% CI: 0.5\u0026ndash;0.7\u003cb\u003e)\u003c/b\u003e, but lower among those residing in rural areas (\u003cb\u003eImputed findings -\u003c/b\u003e A_β = -0.9, 95% CI: -1.0 \u0026ndash; -0.8). Furthermore, female household heads \u003cb\u003e(Imputed findings -\u003c/b\u003e A_β = -0.2, 95% CI: -0.3 \u0026ndash; -0.1\u003cb\u003e)\u003c/b\u003e demonstrated lower levels of aflatoxin-related knowledge compared to their male counterparts. In addition, while the imputed dataset showed a statistically significant association between all SES quintiles and aflatoxin-related knowledge, the CCA indicated significance only in the highest quintile. Nonetheless a similar trend was observed across both analyses whereby aflatoxin-related knowledge increased with increasing wealth (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec and \u003cb\u003eAppendix 3c\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFactors associated with Aflatoxin related Knowledge, Perceptions and Practices (analyses using imputed SES data). (a)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnadjusted OR; 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdjusted OR; 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003ea. Proportion of household heads consuming ugali (maize meal) \u0026ge;3X/Week (logistic regression).\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge of household head.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.999 (0.998\u0026ndash;1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.999 (0.998\u0026ndash;1.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex of household head.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Male\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex of household head (Female).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.010 (0.931\u0026ndash;1.096)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.996 (0.911\u0026ndash;1.089)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidential status household.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Peri-urban\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidential status household (Rural).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.988 (1.851\u0026ndash;2.136)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.947 (1.806\u0026ndash;2.098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold head received formal education.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; No\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold head received formal education (Yes).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.925 (0.860\u0026ndash;0.997)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.994 (0.915\u0026ndash;1.080)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003e8.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSocioeconomic status of household.\u003c/p\u003e \u003cp\u003eQuintile 2\u003c/p\u003e \u003cp\u003eQuintile 3\u003c/p\u003e \u003cp\u003eQuintile 4\u003c/p\u003e \u003cp\u003eQuintile 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Quintile 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.090 (0.981\u0026ndash;1.211)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.009 (0.906\u0026ndash;1.124)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.867\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.067 (0.958\u0026ndash;1.188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.050 (0.941\u0026ndash;1.172)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.109 (0.997\u0026ndash;1.234)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.142 (1.023\u0026ndash;1.275)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.150 (1.033\u0026ndash;1.281)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.322 (1.181\u0026ndash;1.480)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e9.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevel of knowledge of aflatoxin of household head.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.922 (0.912\u0026ndash;0.932)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.936 (0.925\u0026ndash;0.946)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e10.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaize meal consumed is pre-packed or milled locally.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Milled locally\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e11.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaize meal consumed is pre-packed or milled locally (pre-packed).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.002 (0.917\u0026ndash;1.095)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.989 (0.819\u0026ndash;0.985)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e* U_OR \u0026ndash; Unadjusted odds ratio; A_OR \u0026ndash; Adjusted odds ratio; 95% CI \u0026ndash; 95% Confidence Interval.\u003c/b\u003e \u003c/p\u003e\n\u003ch3\u003e(b)\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU_OR; 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA__OR; 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eb. Proportion of household heads that consider aflatoxin when making household food purchases (logistic regression).\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge of household head.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.000 (0.999\u0026ndash;1.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000 (0.998\u0026ndash;1.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.609\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex of household head.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Male\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex of household head (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.804 (0.749\u0026ndash;0.863)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.034 (0.950\u0026ndash;1.126)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.436\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidential status of household.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Peri-urban\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidential status of household (Rural)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.800 (0.753\u0026ndash;0.850)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.136 (1.059\u0026ndash;1.217)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold head received formal education.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; No\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold head received formal education (Yes).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.644 (1.541\u0026ndash;1.755)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.388 (1.282\u0026ndash;1.502)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003e8.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSocioeconomic status of household.\u003c/p\u003e \u003cp\u003eQuintile 2\u003c/p\u003e \u003cp\u003eQuintile 3\u003c/p\u003e \u003cp\u003eQuintile 4\u003c/p\u003e \u003cp\u003eQuintile 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Quintile 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.945 (0.862\u0026ndash;1.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.993 (0.897\u0026ndash;1.099)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.920 (0.837\u0026ndash;1.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.921 (0.829\u0026ndash;1.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.024 (0.934\u0026ndash;1.124)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.975 (0.879\u0026ndash;1.082)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.638\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.371 (1.252\u0026ndash;1.501)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.145 (1.032\u0026ndash;1.271)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e9.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLevel of knowledge of aflatoxin of household head.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.365 (1.349\u0026ndash;1.381)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.361 (1.345\u0026ndash;1.378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e* U_OR \u0026ndash; Unadjusted odds ratio; A_OR \u0026ndash; Adjusted odds ratio; 95% CI \u0026ndash; 95% Confidence Interval.\u003c/b\u003e \u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e(c)\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eU_β; 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eA_β; 95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003ec. Aflatoxin related knowledge score amongst household heads (linear regression).\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge of household head\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001 (-0.001\u0026ndash;0.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.468\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000 (-0.002\u0026ndash;0.002)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex of household head\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Male\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex of household head (Female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.453 (-0.559 \u0026ndash; -0.347)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.186 (-0.299 \u0026ndash; -0.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidential status of household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Peri-urban\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResidential status of household (Rural)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.997 (-1.089 \u0026ndash; -0.906)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.904 (-0.996 \u0026ndash; -0.812)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold head received formal education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; No\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousehold head received formal education (Yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.804 (0.708\u0026ndash;0.900)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.620 (0.516\u0026ndash;0.725)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003e8.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSocioeconomic status of household.\u003c/p\u003e \u003cp\u003eQuintile 2\u003c/p\u003e \u003cp\u003eQuintile 3\u003c/p\u003e \u003cp\u003eQuintile 4\u003c/p\u003e \u003cp\u003eQuintile 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eReference \u0026ndash; Quintile 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.241 (-0.380 \u0026ndash; -0.103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.203 (-0.340 \u0026ndash; -0.066)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.190 (-0.332\u0026ndash;0.049)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.308 (-0.448 \u0026ndash; -0.167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.006 (-0.134\u0026ndash;0.146)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.178 (-0.318 \u0026ndash; -0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.527 (0.387\u0026ndash;0.667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.152 (0.105\u0026ndash;0.294)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e* U_β \u0026ndash; Unadjusted beta coefficient; A_β \u0026ndash; Adjusted beta coefficient; 95% CI \u0026ndash; 95% Confidence Interval.\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eAflatoxins are widespread food contaminants in sub-Saharan Africa (SSA), driven by tropical climates, subsistence farming, limited technology, and weak regulation. Despite their serious health risks, alongside the fact that contamination can occur at any point along the food chain and once introduced, often persists throughout, exposure remains largely underreported due to weak surveillance, limited funding, and low policy prioritization(25). In response to the need for stronger community-level evidence on the aflatoxin exposure risks in Africa, this study represents one of the largest population-based aflatoxin KPP surveys conducted in SSA, providing community-level estimates from nearly 18,000 households in a rural coastal farming community.\u003c/p\u003e \u003cp\u003eOverall, the level of knowledge about aflatoxin was notably low, with less than half of the population having ever heard of it. This low level of awareness of aflatoxin in foods and its health effects has been previously reported in studies comprising members of African households(26\u0026ndash;28). It is reasonable to suggest that a lack of awareness regarding aflatoxin among the study population likely implies the presence of poorly implemented control measures to mitigate contamination and reduce exposure. Indeed, previous surveys among farmers and insights from stakeholders indicate that limited awareness frequently goes hand in hand with poor adoption of aflatoxin control practices(29,30).\u003c/p\u003e \u003cp\u003eOur findings revealed limited awareness of foods at risk of aflatoxin contamination, despite widespread consumption of maize, a staple particularly prone to contamination. In this regard, over three-quarters of the study population were reported to consume maize meal three or more times a week, predominantly sourced from local farming and storage practices. This finding aligns with existing research indicating Kenya's exceptionally high maize consumption rates, estimated to stand at 97 kilograms per capita compared to 76 kilograms per capita in East and Southern Africa(31). This concern is heightened by the rising incidence of hepatocellular carcinoma (HCC) in the African region, alongside the higher rates of HCC in rural areas. Although chronic viral hepatitis B infection has traditionally consistently been reported as the most important cause of HCC in Africa and causal attribution cannot be inferred from this study, our findings suggest that aflatoxin may be a hidden yet significant contributor to this trend warranting closer investigation (32\u0026ndash;34).\u003c/p\u003e \u003cp\u003eAdditionally, there was poor awareness of signs and causes of contamination other than discoloration, as well as the health consequences of aflatoxin exposure, with liver cancer being the least identified health outcome. This observation was of interest given the most severe effect of aflatoxin in the human body is seen in the liver, the organ generally responsible for detoxifying chemical agents and poisons(3). Chronic intake of aflatoxin is strongly linked to HCC largely as a result of the genotoxic carcinogenic effects of aflatoxin(35). It is also widely acknowledged that no level of exposure is entirely safe, consequently levels should be minimized wherever possible(35). Notably, maize and sorghum provided in different forms are often used for weaning children in rural Kenyan populations, meaning exposure often begins early in life and continues into adulthood(31). This establishes a pattern of chronic exposure, which is associated with an increased lifetime risk of liver disease.\u003c/p\u003e \u003cp\u003eMajority (60.8%) of participants aware of aflatoxin, considered it when purchasing flour, often relying on packaging cues such as the KEBS mark of quality. This finding may partly reflect the Hawthorne effect, with participants potentially reporting greater attention to aflatoxin due to awareness of being surveyed on food safety practices. Of note, over half of study participants suggested using media channels to raise awareness of aflatoxin-safe maize flour, highlighting both consumer interest and the potential channels for effective communication to influence purchasing and production practices. Alternatively, fewer than 30% expressed trust in the safety of Kenyan maize flour brands, indicating a need to address public concerns and explore the reasons behind these doubts.\u003c/p\u003e \u003cp\u003eOverall, findings from both complete-case and imputed analyses were consistent, lending support to the assumption that data were missing at random. The higher likelihood of more frequent consumption of maize meal amongst rural populations compared to their peri-urban counterparts is in line with existing observations that point to maize as a staple food in Kenya overall and particularly in rural areas, where it is grown in ninety percent of farms(36). The lower odds of consuming maize meal three or more times per week among households purchasing pre-packed maize, compared with those relying on locally milled maize, further support this pattern. Interestingly high SES households (quintile 4 and 5) were noted to consume maize meal more frequently than their lower SES counterparts, suggesting a sustained preference for ugali even as households move up the wealth ladder, with the key transition being a shift from locally milled to pre-packaged maize meal (37).\u003c/p\u003e \u003cp\u003eSimilarly, rural households and those of higher-SES were more likely to consider aflatoxin contamination when purchasing food compared to peri-urban and lower-SES households. This occurred despite lower aflatoxin knowledge among rural household heads. A possible explanation is that rural, largely agricultural communities are more directly exposed to the visible consequences of poor farming, storage, and handling practices, such as mouldy grains. This lived experience may encourage caution when buying maize meal, even if technical knowledge is limited. Supporting this, a study in Western Kenya found that while only 20% of rural caregivers had heard of aflatoxins, over 60% recognized visual spoilage indicators (e.g., mould, dampness) and linked them to crop spoilage and potential causes(38). Additionally, individuals who had ever attended school as well as those of higher SES (quintile 5) also appeared to consider aflatoxin contamination more commonly than their counterparts, a fact likely influenced by a greater awareness and purchasing power, enabling them to prioritize food safety(39).\u003c/p\u003e \u003cp\u003eInterestingly, although women play a significant role in agricultural and post-harvest activities, including food preparation(40), female household heads demonstrated lower levels of aflatoxin-related knowledge than their male counterparts. Similar findings have been reported in studies from other SSA countries, including Nigeria and other areas of Kenya, suggesting a broader regional pattern(26,41). The observed association, where aflatoxin-related knowledge increased with higher SES and school attendance but was lower among rural and female household heads, may reflect disparities in access to education, information, and resources, such as agricultural extension services.\u003c/p\u003e \u003cp\u003eIt is important to acknowledge that this study is not without its limitations. Firstly, we must acknowledge the potential for social desirability bias. The exclusive use of quantitative methods also limited in-depth understanding of participants\u0026rsquo; perceptions, such as concerns about Kenyan maize flour, and agricultural practices which are central to aflatoxin risk. Though the latter was not explored in this study, complementary data from a subsample of smallholder farmers offers additional insights (18). Despite these limitations, the study has strengths that enhance its credibility, including a census-based sampling approach with a high response rate and engagement of respected CHPs, enabling contextual understanding.\u003c/p\u003e \u003cp\u003eAflatoxin remains a critical global food safety concern, disproportionately affecting rural subsistence farming communities in LMICs. Our findings emphasize the need to raise aflatoxin awareness in rural farming populations, particularly among women, potentially by engaging agricultural extension workers or civil society and community-based organizations to strengthen literacy, promote safe food handling practices, and ultimately reduce exposure. Importantly, limited dietary diversity (potentially driven by food insecurity) further increases vulnerability to aflatoxin exposure and its associated health effects. This reality is highly relevant to our study population, where nearly 70% live below the poverty line. Taken together, these findings emphasize the need for multifaceted interventions that raise awareness, improve food handling practices, and address underlying food security challenges as well as dietary behaviour, providing a roadmap for reducing aflatoxin exposure and its health impacts in vulnerable rural communities.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAdjusted beta coefficient\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eA_β\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAdjusted odds ratio\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eA_OR\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAspergillus flavus\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eA. flavus\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAspergillus parasiticus\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eA. parasiticus\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eComma\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSeparated Values\u0026ndash;CSV\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCommunity Health Promoters\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCHPs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eComplete\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecase analysis\u0026ndash;CCA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDemographic and Health Surveillance\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDHS\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHepatocellular carcinoma\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHCC\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKaloleni Rabai Health and Demographic Surveillance System\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKRHDSS\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKenya Bureau of Standards\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKEBS\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKnowledge Perception Practice\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKPP\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLow\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eand\u0026ndash;middle\u0026ndash;income countries\u0026ndash;LMICs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMultiple imputation\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMI\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNational Commission for Science, Technology and Innovation\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNACOSTI\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSocioeconomic status\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSES\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eStandard deviation\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003esub\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSaharan Africa\u0026ndash;SSA\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUnadjusted beta coefficient\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eU_β\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUnadjusted odds ratio\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eU_OR\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e95% Confidence Interval\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003col start=\"1\" type=\"I\"\u003e\n \u003cli\u003eETHICS APPROVAL AND CONSENT TO PARTICIPATE\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe study was approved by the Aga Khan University Institutional Scientific and Ethical Review Committee (AKU-ISERC) (2013/IREC-65(v10)) and undertaken in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003col start=\"2\" type=\"I\"\u003e\n \u003cli\u003eCONSENT FOR PUBLICATION\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWritten informed consent was obtained from all study participants, including consent to publish study findings.\u003c/p\u003e\n\u003col start=\"3\" type=\"I\"\u003e\n \u003cli\u003eAVAILABILITY OF DATA AND MATERIALS\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAny interested parties can apply directly to the corresponding author to access the data used in this paper by contacting them at [email protected]\u003c/p\u003e\n\u003col start=\"4\" type=\"I\"\u003e\n \u003cli\u003eCOMPETING INTERESTS\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe Authors declare that there is no \u0026lsquo;conflict of interest\u0026rsquo;.\u003c/p\u003e\n\u003col start=\"5\" type=\"I\"\u003e\n \u003cli\u003eFUNDING\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors. This work was supported through internal university funding made available by the Aga Khan University (AKU) Department of Haematology and Oncology (DHO) and Kaloleni-Rabai Health and Demographic Surveillance System (KRHDSS).\u003c/p\u003e\n\u003col start=\"6\" type=\"I\"\u003e\n \u003cli\u003eAUTHOR CONTRIBUTIONS\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026quot;RIO provided input in the design of this study protocol, oversaw the implementation of this study and was responsible for analysis of data as well as finding relevant literature and leading drafting of this manuscript.\u0026quot;\u003c/p\u003e\n\u003cp\u003e\u0026quot;JA provided input in the review and editing of the manuscript.\u0026quot;\u003c/p\u003e\n\u003cp\u003e\u0026quot;AN provided input in the design of this study protocol, implementation of the study protocol and drafting of this manuscript.\u0026quot;\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;IA provided input in the design of this study protocol, participated in development of the data collection tool, implementation of this study as well as review and editing of the manuscript.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u0026quot;MS led acquisition of funding for this study as well as participated in development of the study protocol and data collection tool as well as review and editing of the manuscript.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u0026quot;All authors read and approved the final manuscript.\u0026quot;\u003c/p\u003e\n\u003col start=\"7\" type=\"I\"\u003e\n \u003cli\u003eACKNOWLEDGMENTS\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWe gratefully acknowledge the support from Kaloleni-Rabai leadership, as well as the participating Community Health Units, and their teams of Community Health Promoters.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eShabeer S, Asad S, Jamal A, Ali A. Aflatoxin Contamination, Its Impact and Management Strategies: An Updated Review. Toxins (Basel) [Internet]. 2022 Apr 27 [cited 2025 Oct 7];14(5):307. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9147583/\u003c/li\u003e\n\u003cli\u003ePACA. Aflatoxin Impacts and Potential Solutions in Agriculture, Trade, and Health. A Background Paper for the PACA Strategy Development – Stakeholder Consultation Workshop [Internet]. 2013 Apr [cited 2025 Oct 7]; Available from: https://archives.au.int/handle/123456789/4985\u003c/li\u003e\n\u003cli\u003eDhakal A, Hashmi MF, Sbar E. Aflatoxin Toxicity. In: StatPearls [Internet] [Internet]. StatPearls Publishing; 2023 [cited 2025 Oct 7]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK557781/\u003c/li\u003e\n\u003cli\u003eThe Menace of Aflatoxin: Understanding the Effects of Contamination by Aspergillus Species on Crops and Human Health and Advancements in Managing These Toxic Metabolites | IntechOpen [Internet]. [cited 2025 Oct 7]. Available from: https://www.intechopen.com/chapters/86885\u003c/li\u003e\n\u003cli\u003eAlvarado AM, Zamora-Sanabria R, Granados-Chinchilla F, Alvarado AM, Zamora-Sanabria R, Granados-Chinchilla F. A Focus on Aflatoxins in Feedstuffs: Levels of Contamination, Prevalence, Control Strategies, and Impacts on Animal Health. In: Aflatoxin - Control, Analysis, Detection and Health Risks [Internet]. IntechOpen; 2017 [cited 2025 Oct 7]. Available from: https://www.intechopen.com/chapters/56001\u003c/li\u003e\n\u003cli\u003eBenkerroum N, Ismail A. Human Breast Milk Contamination with Aflatoxins, Impact on Children’s Health, and Possible Control Means: A Review. Int J Environ Res Public Health [Internet]. 2022 Dec 14 [cited 2025 Oct 7];19(24):16792. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9779431/\u003c/li\u003e\n\u003cli\u003eWangia RN, Githanga DP, Wang JS, Anzala OA. Aflatoxin exposure in children age 6–12 years: a study protocol of a randomized comparative cross-sectional study in Kenya, East Africa. Pilot and Feasibility Studies [Internet]. 2019 Nov 29 [cited 2025 Oct 7];5(1):141. Available from: https://doi.org/10.1186/s40814-019-0510-x\u003c/li\u003e\n\u003cli\u003eHumans IWG on the E of CR to. AFLATOXINS. In: Chemical Agents and Related Occupations [Internet]. International Agency for Research on Cancer; 2012 [cited 2025 Oct 7]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK304413/\u003c/li\u003e\n\u003cli\u003eSmith LE, Prendergast AJ, Turner PC, Humphrey JH, Stoltzfus RJ. Aflatoxin Exposure During Pregnancy, Maternal Anemia, and Adverse Birth Outcomes. Am J Trop Med Hyg [Internet]. 2017 Apr 5 [cited 2025 Oct 7];96(4):770–6. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC5392618/\u003c/li\u003e\n\u003cli\u003eRasheed H, Xu Y, Kimanya ME, Pan X, Li Z, Zou X, et al. Estimating the health burden of aflatoxin attributable stunting among children in low income countries of Africa. Sci Rep [Internet]. 2021 Jan 15 [cited 2025 Oct 7];11(1):1619. Available from: https://www.nature.com/articles/s41598-020-80356-4\u003c/li\u003e\n\u003cli\u003eMukasa AN, Woldemichael AD, Salami AO, Simpasa AM. Africa’s Agricultural Transformation: Identifying Priority Areas and Overcoming Challenges. 2017;8(3).\u003c/li\u003e\n\u003cli\u003eNji QN, Babalola OO, Ekwomadu TI, Nleya N, Mwanza M. Six Main Contributing Factors to High Levels of Mycotoxin Contamination in African Foods. Toxins (Basel) [Internet]. 2022 Apr 29 [cited 2025 Oct 7];14(5):318. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9146326/\u003c/li\u003e\n\u003cli\u003eBunny SM, Umar A, Bhatti HS, Honey SF. Aflatoxin risk in the era of climatic change-a comprehensive review. CABI Agriculture and Bioscience [Internet]. 2024 Nov 9 [cited 2025 Oct 7];5(1):105. Available from: https://doi.org/10.1186/s43170-024-00305-3\u003c/li\u003e\n\u003cli\u003eOmara T, Kiprop AK, Wangila P, Wacoo AP, Kagoya S, Nteziyaremye P, et al. The Scourge of Aflatoxins in Kenya: A 60-Year Review (1960 to 2020). [cited 2025 Oct 7]; Available from: https://onlinelibrary.wiley.com/doi/10.1155/2021/8899839\u003c/li\u003e\n\u003cli\u003eYard EE, Daniel JH, Lewis LS, Rybak ME, Paliakov EM, Kim AA, et al. Human aflatoxin exposure in Kenya, 2007: a cross-sectional study. Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2013;30(7):1322–31.\u003c/li\u003e\n\u003cli\u003eAgriculture M of, Fisheries L and, Kenya. Climate Risk Profile for Kilifi County. Kenya County Climate Risk Profile Series. 2016 [cited 2025 Oct 7]; Available from: https://hdl.handle.net/10568/80453\u003c/li\u003e\n\u003cli\u003eKilifi County CC Action Plan (2023–2027) Reviewed (1).pdf [Internet]. [cited 2025 Oct 7]. Available from: https://maarifa.cog.go.ke/sites/default/files/2024-07/Kilifi%20County%20CC%20Action%20Plan%20%282023-2027%29%20Reviewed%20%281%29.pdf\u003c/li\u003e\n\u003cli\u003eIseme-Ondiek R, Mwangi EM, Riang’a RM, Agoi F, Khatievi N, Orwa J, et al. The association between food production, food security, household consumer behaviour and waist-hip ratio amongst women in smallholder farming households in Kilifi County, Kenya. [cited 2025 Aug 8]; Available from: https://onlinelibrary.wiley.com/doi/10.1111/nbu.12718\u003c/li\u003e\n\u003cli\u003eAnthonj C, Bianchi F, Cadum E, Anthonj C. Risk Perception and COVID-19. 2020 May 7 [cited 2025 Oct 22]; Available from: https://www.preprints.org/manuscript/202005.0132\u003c/li\u003e\n\u003cli\u003eTerpstra T, Lindell MK, Gutteling JM. Does Communicating (Flood) Risk Affect (Flood) Risk Perceptions? Results of a Quasi-Experimental Study. Risk Analysis [Internet]. 2009 [cited 2025 Oct 22];29(8):1141–55. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1539-6924.2009.01252.x\u003c/li\u003e\n\u003cli\u003eAnthony N, Rachel O, Felix A, Amyn L, James O, Jerim O, et al. Cohort Profile: The Kaloleni/Rabai Community Health and Demographic Surveillance System. International journal of epidemiology [Internet]. 2020 Jun 1 [cited 2023 Jul 31];49(3). Available from: https://pubmed.ncbi.nlm.nih.gov/31872230/\u003c/li\u003e\n\u003cli\u003eNgugi AK, Walraven G, Orwa J, Lusambili A, Kimani M, Luchters S. Community-driven data revolution is feasible in developing countries: experiences from an integrated health information and surveillance system in Kenya. Journal of Global Health Reports [Internet]. 2021 Aug 9 [cited 2023 Jul 31];5:e2021074. Available from: https://www.joghr.org/article/25977-community-driven-data-revolution-is-feasible-in-developing-countries-experiences-from-an-integrated-health-information-and-surveillance-system-in-ken\u003c/li\u003e\n\u003cli\u003eOliver M, Geniets A, Winters N, Rega I, Mbae SM. What do community health workers have to say about their work, and how can this inform improved programme design? A case study with CHWs within Kenya. Glob Health Action [Internet]. 2015 May 22 [cited 2025 Oct 22];8:10.3402/gha.v8.27168. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4442123/\u003c/li\u003e\n\u003cli\u003eStataCorp LLC. STATA. StataCorp LP, College Station; 2013. (Stata Statistical Software).\u003c/li\u003e\n\u003cli\u003eOkoth S. Improving the evidence base on aflatoxin contamination and exposure in Africa. 2016 [cited 2025 Oct 22]; Available from: https://hdl.handle.net/10568/90118\u003c/li\u003e\n\u003cli\u003eFalade TDO, Kadjo D, Ortega-Beltran A, Atser G, Sanni L. Knowledge, perceptions and practices regarding aflatoxins and aflatoxin management solutions among women: a perspective from two communities in Nigeria. 2025 Feb [cited 2025 Oct 22]; Available from: https://hdl.handle.net/10568/175835\u003c/li\u003e\n\u003cli\u003eTsegaye SH, Itafa BT. Smallholders’ knowledge, attitude, and practices towards aflatoxins contamination in animal feeds. Dairy Sci Manag [Internet]. 2025 Dec [cited 2025 Oct 22];2(1):1–10. Available from: https://dairysciencemanagement.biomedcentral.com/articles/10.1186/s44363-025-00007-9\u003c/li\u003e\n\u003cli\u003eCheruiyot C, Okoth MW, Abong’ GO, Kariuki SW. Knowledge, Attitudes, and Food Safety Practices of Informal Market Maize Grain Vendors and Consumers in Meru County, Kenya. International Journal of Food Science [Internet]. 2024 [cited 2025 Oct 22];2024(1):6592430. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1155/ijfo/6592430\u003c/li\u003e\n\u003cli\u003eFundikira S, Suleiman R, De Saeger S, De Boevre M, Kimanya M. Aflatoxin awareness and preventive agricultural practices are key to adoption of biocontrol among maize smallholder farmers in Tanzania. Mycotoxin Res [Internet]. 2025 Feb 1 [cited 2025 Oct 22];41(1):179–89. Available from: https://doi.org/10.1007/s12550-024-00574-x\u003c/li\u003e\n\u003cli\u003eLimited knowledge and lack of access to appropriate technologies inhibiting aflatoxin prevention and control in East Africa [Internet]. [cited 2025 Oct 22]. Available from: https://www.eac.int/press-releases/141-agriculture-food-security/2888-limited-knowledge-and-lack-of-access-to-appropriate-technologies-inhibiting-aflatoxin-prevention-and-control-in-east-africa\u003c/li\u003e\n\u003cli\u003eKang’ethe EK, Gatwiri M, Sirma AJ, Ouko EO, Mburugu-Musoti CK, Kitala PM, et al. Exposure of Kenyan population to aflatoxins in foods with special reference to Nandi and Makueni counties. [cited 2025 Oct 22]; Available from: https://dx.doi.org/10.1093/fqsafe/fyx011\u003c/li\u003e\n\u003cli\u003eKedar Mukthinuthalapati VVP, Sewram V, Ndlovu N, Kimani S, Abdelaziz AO, Chiao EY, et al. Hepatocellular Carcinoma in Sub-Saharan Africa. JCO Glob Oncol [Internet]. 2021 May 27 [cited 2025 Oct 23];7:GO.20.00425. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC8457845/\u003c/li\u003e\n\u003cli\u003eEl-Kassas M, Elbadry M. Hepatocellular Carcinoma in Africa: Challenges and Opportunities. Front Med (Lausanne) [Internet]. 2022 Jun 24 [cited 2025 Nov 5];9:899420. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9263092/\u003c/li\u003e\n\u003cli\u003eMann EM, Akambase J, Searle K, Hunt S, Debes JD. Differential Association of Hepatocellular Carcinoma Related to Hepatitis B Between Urban and Rural Areas in Africa Using Satellite Spatial Scaling Data. JCO Glob Oncol [Internet]. 2025 Apr [cited 2025 Nov 5];(11):e2400543. Available from: https://ascopubs.org/doi/10.1200/GO-24-00543\u003c/li\u003e\n\u003cli\u003eThe aflatoxin situation in Africa: Systematic literature review - Meijer − 2021 - Comprehensive Reviews in Food Science and Food Safety - Wiley Online Library [Internet]. [cited 2025 Oct 22]. Available from: https://ift.onlinelibrary.wiley.com/doi/full/10.1111/1541-4337.12731\u003c/li\u003e\n\u003cli\u003eUnlocking Employment Opportunities in Kenya’s Maize Value Chain – KIPPRA [Internet]. [cited 2025 Oct 22]. Available from: https://kippra.or.ke/unlocking-employment-opportunities-in-kenyas-maize-value-chain/\u003c/li\u003e\n\u003cli\u003eH DG, Sc K. Consumer preferences for maize products in urban Kenya. Food and nutrition bulletin [Internet]. 2012 Jun [cited 2025 Oct 22];33(2). Available from: https://pubmed.ncbi.nlm.nih.gov/22908691/\u003c/li\u003e\n\u003cli\u003eAwuor AO, Wambura G, Ngere I, Hunsperger E, Onyango C, Bigogo G, et al. A mixed methods assessment of knowledge, attitudes and practices related to aflatoxin contamination and exposure among caregivers of children under 5 years in western Kenya. Public Health Nutr [Internet]. [cited 2025 Aug 27];26(12):3013–22. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10755389/\u003c/li\u003e\n\u003cli\u003eAyo E, Matemu A, Laswai G, Kimanya M. Socioeconomic Characteristics Influencing Level of Awareness of Aflatoxin Contamination of Feeds among Livestock Farmers in Meru District of Tanzania. 2018 Apr 30 [cited 2025 Oct 22]; Available from: https://dspace.nm-aist.ac.tz/handle/20.500.12479/1081\u003c/li\u003e\n\u003cli\u003eOnyalo PO. WOMEN AND AGRICULTURE IN RURAL KENYA: ROLE IN AGRICULTURAL PRODUCTION. 2019;4.\u003c/li\u003e\n\u003cli\u003eCheruiyot C, Okoth MW, Abong’ GO, Kariuki SW. Knowledge, Attitudes, and Food Safety Practices of Informal Market Maize Grain Vendors and Consumers in Meru County, Kenya. Int J Food Sci [Internet]. 2024 Nov 21 [cited 2025 Oct 22];2024:6592430. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC11606682/\u003c/li\u003e\n\u003cli\u003eAPPENDICES\u003c/li\u003e\n\u003cli\u003e\u003cb\u003eAPPENDIX 1\u003c/b\u003e: Exploration of Missing Data Patterns\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Aflatoxin, Population-based survey, Rural community, Health risks, Cancer risks","lastPublishedDoi":"10.21203/rs.3.rs-8785894/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8785894/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBACKGROUND\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAflatoxin contamination is a significant yet under-addressed food safety challenge in low-resource settings, driven by a complex interplay of environmental, agricultural, and socio-economic factors. Limited access to agricultural inputs, inadequate post-harvest handling and storage, and weak regulatory enforcement alongside food scarcity and climate change heighten the risk of contamination and exposure. Human exposure is associated with serious health consequences, including hepatocellular carcinoma, immune suppression, and childhood stunting. Although aflatoxin is increasingly recognized as a global food safety concern, little is known about community-level knowledge, risk perceptions, and preventive practices. This study examined household heads\u0026rsquo; awareness, perceptions, and behaviours related to aflatoxin exposure and mitigation in a rural coastal community in Kenya.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMETHODS\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe conducted a cross-sectional survey using a census approach within the Kaloleni-Rabai Health and Demographic Surveillance System (KRHDSS). Between July and December 2022, data were collected from 17,813 household heads through face-to-face, interviewer-administered, digitized questionnaires.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRESULTS\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFarming was the predominant occupation (n\u0026thinsp;=\u0026thinsp;5,757; 32.3%). Maize was sourced primarily from household harvests and local markets, with over three-quarters (n\u0026thinsp;=\u0026thinsp;13,818; 77.6%) of respondents consuming maize flour three or more times weekly. Despite maize being a dietary staple, awareness of aflatoxin was limited: only 49.5% (n\u0026thinsp;=\u0026thinsp;8,816) had heard of aflatoxin. Even fewer (\u0026lt;\u0026thinsp;20%) respondents were able to identify foods at risk, signs of contamination, causes of fungal growth, or health consequences of exposure. Socio-economic status, rurality, education, and sex influenced aflatoxin-related knowledge, perceptions, and practices.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCONCLUSION\u003c/b\u003e\u003c/p\u003e \u003cp\u003eLow awareness of aflatoxin constrains rural households\u0026rsquo; ability to prevent contamination and limit exposure. As aflatoxin risk arises at multiple points along the agricultural value chain, and vulnerability to exposure is heightened during periods of food scarcity, comprehensive approaches are required. Effective prevention will depend on integrated strategies that combine educational initiatives, infrastructural support, and policy interventions targeting agricultural practices, food security, and consumer behaviours.\u003c/p\u003e","manuscriptTitle":"Assessing Aflatoxin Knowledge, Perceptions, and related Practices, in a Rural Coastal Community: A Population-Based Cross-sectional Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 10:09:55","doi":"10.21203/rs.3.rs-8785894/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-17T09:59:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-14T18:32:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4150281061504692815755884530852632354","date":"2026-03-11T10:47:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-10T12:39:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"277162723279490072239912323007442322374","date":"2026-03-10T12:30:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-09T09:41:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214442172813543739804489058818117857313","date":"2026-02-16T05:14:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263946427238294806655571117335965087226","date":"2026-02-14T10:05:07+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-12T09:47:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-12T09:36:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-09T11:30:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-06T12:26:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-06T11:55:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d3e19221-9eb4-4d7b-87b5-d9c9c95dd959","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T09:11:19+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 10:09:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8785894","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8785894","identity":"rs-8785894","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}