Baseline associations between exposure to metals and systolic and diastolic blood pressure among women in the Household Air Pollution Intervention Network Trial

Baseline associations between exposure to metals and systolic and diastolic blood pressure among women in the Household Air Pollution Intervention Network Trial | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Baseline associations between exposure to metals and systolic and diastolic blood pressure among women in the Household Air Pollution Intervention Network Trial View ORCID Profile Patrick Karakwende , Dana Boyd Barr , View ORCID Profile William Checkley , Thomas Clasen , Amy Lovvorn , Carmen Lucía Contreras , Anaite A. Diaz , Ephrem Dusabimana , View ORCID Profile Lisa De Las Fuentes , Shirin Jabbarzadeh , Michael Johnson , Egide Kalisa , Miles Kirby , John P. McCracken , Florien Ndagijimana , Adolphe Ndikubwimana , View ORCID Profile Theoneste Ntakirutimana , View ORCID Profile Jean de Dieu Ntivuguruzwa , L Jennifer , Ajay Pillarisetti Peel , Victor G. Davila-Roman , Ghislaine Rosa , View ORCID Profile Lance A. Waller , Jiantong Wang , Lisa Thompson , Maggie L. Clark , Bonnie N. Young the HAPIN investigators , the HAPIN investigators doi: https://doi.org/10.1101/2025.01.21.25320894 Patrick Karakwende 1 School of Public Health, College of Medicine and Health Sciences, University of Rwanda , Kigali Rwanda Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Patrick Karakwende Dana Boyd Barr 2 Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, GA, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site William Checkley 3 Division of Pulmonary and Critical Care, and the Center for Non-Communicable Disease Research and Training, School of Medicine, Johns Hopkins University , Baltimore, MD US Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for William Checkley Thomas Clasen 2 Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, GA, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site Amy Lovvorn 2 Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University , Atlanta, GA, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site Carmen Lucía Contreras 4 Center for Health Studies, Universidad del Valle de Guatemala , Guatemala City, Guatemala Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anaite A. Diaz 4 Center for Health Studies, Universidad del Valle de Guatemala , Guatemala City, Guatemala Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ephrem Dusabimana 5 Eagle Research Center , Kigali, Rwanda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lisa De Las Fuentes 4 Center for Health Studies, Universidad del Valle de Guatemala , Guatemala City, Guatemala Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lisa De Las Fuentes Shirin Jabbarzadeh 6 Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University , Atlanta, GA, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site Michael Johnson 7 Berkeley Air Monitoring Group , Berkeley, CA USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Egide Kalisa 8 School of Sciences, Center of Excellence in Biodiversity and Natural Resource Management, College of Science and Technology , Kigali, Rwanda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Miles Kirby 9 Harvard University , Cambridge, MA, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site John P. McCracken 4 Center for Health Studies, Universidad del Valle de Guatemala , Guatemala City, Guatemala 10 Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia , Athens, GA, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site Florien Ndagijimana 5 Eagle Research Center , Kigali, Rwanda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Adolphe Ndikubwimana 1 School of Public Health, College of Medicine and Health Sciences, University of Rwanda , Kigali Rwanda Find this author on Google Scholar Find this author on PubMed Search for this author on this site Theoneste Ntakirutimana 1 School of Public Health, College of Medicine and Health Sciences, University of Rwanda , Kigali Rwanda Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Theoneste Ntakirutimana Jean de Dieu Ntivuguruzwa 5 Eagle Research Center , Kigali, Rwanda Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Jean de Dieu Ntivuguruzwa L Jennifer 11 Department of Environmental and Radiological Health Sciences, Colorado State University , Fort Collins, CO, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ajay Pillarisetti Peel 12 Division of Environmental Health Sciences, School of Public Health, University of California , Berkeley, California, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Victor G. Davila-Roman 13 Caridiovascular Division, School of Medicine, Washington University School of Medicine St. Louis , MO Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ghislaine Rosa 14 Department of Infectious and Tropical Diseases, Liverpool School of Tropical Medicine , Liverpoold, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lance A. Waller 6 Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University , Atlanta, GA, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Lance A. Waller Jiantong Wang 6 Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University , Atlanta, GA, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lisa Thompson 15 Nell Hodgson Woodruff School of Nursing Emory University 1520 Clifton Road , NE Atlanta, GA 30322-4027 Find this author on Google Scholar Find this author on PubMed Search for this author on this site Maggie L. Clark 11 Department of Environmental and Radiological Health Sciences, Colorado State University , Fort Collins, CO, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site Bonnie N. Young 11 Department of Environmental and Radiological Health Sciences, Colorado State University , Fort Collins, CO, US Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: bonnie.young{at}colostate.edu Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Lead (Pb) and cadmium (Cd) are metals that occur naturally in the environment and are present in biomass fuels, such as wood. When these fuels are burned, they can release Pb and Cd into the air, leading to exposure through inhalation. Studies of exposure to metals and health outcomes suggest harmful impacts, including cardiovascular diseases. We assessed baseline associations between Pb and Cd concentrations in dried blood spots with systolic and diastolic blood pressure (SBP, DBP) among women in the Household Air Pollution Intervention Network (HAPIN) trial. We analyzed data from three of the four HAPIN randomized controlled trial sites (Guatemala, Peru, and Rwanda), focusing on women aged 40 to 79 years living in households reliant on biomass cooking. Dried blood spots were collected, processed, and analyzed for Pb and Cd exposure; SBP and DBP were measured following international guidelines. Demographic, socioeconomic, and dietary variables were collected via standardized questionnaires administered by local field staff. Statistical analyses included multivariable linear regression to examine associations between Pb and Cd, separately, and BP, adjusting for covariates informed by a Directed Acyclic Graph. Additional analyses assessed effect modification by age and research site. There was regional variation in BP levels among women, with median SBP and DBP values higher in Rwanda (116.3 mmHg, 73.0 mmHg) and Guatemala (113.3 mmHg, 68.3 mmHg) compared to Peru (106.0 mmHg, 63.3 mmHg). Pb exposure showed positive associations with both SBP and DBP. For each log-unit increase in Pb concentration, we observed increases of 2.36 mmHg SBP (95% CI 0.51, 4.20) and 1.42 mmHg DBP (95% CI 0.16, 2.67). Cd was not associated with SBP or DBP in this analysis. Pb exposure may be an important risk factor for increased SBP and DBP, markers of cardiovascular disease risk. 1. Introduction Lead (Pb) and cadmium (Cd) are metals that occur naturally in the environment and are in biomass fuels, such as wood. When burned, these fuels can release Pb and Cd into the air, leading to exposure 1 . Studies on associations between exposure to these metals and health conditions suggest harmful impacts on health including cardiovascular diseases, as exposure to both Pb and Cd have been shown to be considered coronary risk factors 2 . Evidence indicates that metal levels in the body change with age due to differences in exposure sources, absorption rates, and cumulative effects 3 . Adults, particularly older adults, may experience chronic health effects due to long-term exposure and bioaccumulation 4 . Cd is considered a toxic pollutant due to its carcinogenic and mutagenic properties. Exposure to even low levels of Cd can affect the brain, kidneys, and heart and even result in death 5 . In a systematic review conducted by Bret Ericson et al identified major sources of lead exposure as informal lead acid battery recycling and manufacture, metal mining and processing, electronic waste, and the use of lead as a food adulterant, primarily in spices among others 6 . There are a few suggested pathways for how Pb and Cd exposure can impact cardiovascular disease risk. Pb and Cd can lead to problems with blood coagulation 7 and can disrupt the normal functioning of blood vessels and the heart. Pb, for example, can interfere with the regulation of blood pressure (BP) by affecting kidney function and the nervous system 8 . Exposure to these metals has been associated with an increased risk of hypertension, a major risk factor for heart attacks and strokes 9 . Chronic exposure to Pb and Cd may lead to sustained increases in BP, contributing to long-term health issues 10 . This can also result in a cycle of health decline, where hypertension exacerbates other conditions 11 . Elevated BP can serve as an early indicator of potential health impacts from environmental exposure to these heavy metals, helping in the development of preventive measures and policies 12 . Exposure to Pb has been linked to elevated BP, primarily due to its toxic effects on the cardiovascular system. Pb interferes with calcium signaling, which is crucial for maintaining vascular tone and blood pressure regulation. It promotes oxidative stress and inflammation, leading to endothelial dysfunction and reduced nitric oxide availability, both of which impair the relaxation of blood vessels. Additionally, Pb can stimulate the sympathetic nervous system, increasing heart rate and vascular resistance. Chronic exposure may also impair kidney function, disrupting fluid and electrolyte balance, further contributing to hypertension. These combined mechanisms underscore the role of Pb exposure as a risk factor for high blood pressure 13 . Our aim was to assess baseline associations of Pb and Cd concentrations from dried blood spots with systolic and diastolic BP (SBP, DBP) among women aged 40-79 years among 3 research sites (Guatemala, Peru, Rwanda) of the Household Air Pollution Intervention Network (HAPIN) trial. We hypothesized that SBP and DBP would be positively associated increases with higher Pb and Cd concentrations. 2. Materials and Methods 2.1. Study site and population This paper analyzed data from the HAPIN trial from 3 of the 4 countries (Guatemala, Peru, and Rwanda, excluding India), which has been described in detail by Clasen et al 14 . Briefly, the HAPIN trial was a randomized controlled trial to investigate the effect of a liquefied petroleum gas (LPG) cookstove and fuel intervention on exposure to household air pollution and health. For this analysis, we assessed the association of Pb and Cd exposure on BP in women residing with pregnant women enrolled in the HAPIN trial. This analysis included non-pregnant adult female participants at baseline (before households were randomly assigned to intervention or control arms, stratified by country) in the HAPIN trial research sites (Guatemala, Peru and Rwanda). Personal exposures to metals and health outcomes were obtained from 272 adult women aged 40 to 79 years (confirmed by government-issued identification card when possible) who resided in the same households as an enrolled pregnant woman in the HAPIN trial across study sites, provided they did not meet any of the following exclusion criteria: currently smoking cigarettes or other tobacco products, or planning to permanently move out of their current household in the next 12 months. Households were included in the study if they self-reported primarily using biomass fuels for cooking 15 . The study sites were selected because solid biomass was the primary source of fuel for a large proportion of the population. The study participants in Guatemala were characterized by the use of chimney stoves and open fires; 97% used wood fuel and cooked mainly indoors 16 . In Peru, study participants came from rural households that regularly cooked using traditional biomass (usually dung mixed with straw) burning stoves 17 . In Rwanda, 80.4% of the population relied on wood or wood-based products for cooking, which was typically done on traditional open stoves in poorly ventilated kitchens, in addition to the traditional three stone fires (62.6%) or clay brazier stove (34.6%) fueled with wood (89.9%) or charcoal (8.1%) and cooking indoors (71.9%) 18 . 2.2. Clinical Biomarkers and BP Measurements Following recruiting and informed consent, qualified fieldworkers visited the families at the start of the study to do baseline questionnaires and other evaluations. Dried blood spots were collected immediately after 24-hour household air pollution exposure measurements using a GE Whatman 903 Protein Saver Card and a BD contact-activated 2.0 mm lancet. Technicians performed finger-stick punctures on participants’ non-dominant hand, cleaning the site with 70% isopropanol to ensure sample integrity. Blood was collected by gently massaging the hand to promote flow, without squeezing, and drops were allowed to fall naturally onto the filter paper. After drying at room temperature for 24-48 hours, the blood spots were stored in biospecimen bags with desiccants and humidity indicator cards at -20°C, shipped on dry ice, and analyzed at Emory University. Invalid spots were marked to guide lab processing, and valid spots were carefully selected for analysis. At Emory University, dried blood spot samples from Guatemala, Rwanda, and Peru were analyzed using inductively coupled plasma mass spectrometry (ICP-MS) after digestion with nitric acid. A range of quality controls, including laboratory blanks and reference materials, was used to ensure accuracy. Samples were standardized for blood volume and analyzed for elements such as Pb and Cd, with strict quality control measures in place. For the potassium standardization of Pb and Cd concentrations, each metal value was multiplied by 4 mmol/mL and then divided by the individual’s specific potassium value: (metal*4)/K+. BP measurements were recorded using an Omron HEM-907XL monitor, with three measurements taken after ensuring participants had not smoked, consumed alcohol or caffeine, or cooked with biomass in the last 30 minutes 14 . 2.3. Other variables Qualified fieldworkers visited the households at the beginning of the study to conduct baseline surveys and other assessments after recruitment and informed consent. Interviews and surveys were conducted in the participant’s native language by research assistants. This baseline visit included a survey covering a range of topics like cooking behaviors, household composition, socioeconomic status (SES) and demographic information like age in years that was confirmed by national ID card, education which was self-reported and split into no formal education; primary or secondary incomplete; and secondary, college or university categories. Women self-reported exposure to secondhand tobacco (yes/no). We determined dietary diversity using the Minimum Dietary Diversity for Women (MDD-W) indicator, which is based on ten food groups (FAO FHI 360, 2016). Diet diversity was considered low if the participant had consumed less than four of the ten food groups over the previous 30 days (MDD-W 5). Food insecurity was assessed by the use Food Insecurity Experience Scale, developed by the Food and Agriculture Organization of the United Nations, http://www.fao.org/3/as583e/as583e.pdf . Material items were selected as useful indicators of SES by other HAPIN investigators to be used across all publications. SES items included color TV, radio, mobile phone, bank account, and bicycle (yes/no per item). We measured weight and height in duplicate using seca 876 electronic scales and seca 213 stadiometer platforms (seca GmbH & Co. KG., Hamburg, Germany), respectively. If the weight or height measurements differed by more than 0.5 kg or 1 cm, respectively, we collected a third measurement and the two closest readings were averaged. We computed BMI as the ratio between weight and height-squared (kg/m2). We determined level of physical activity using the Global Physical Activity Questionnaire (GPAQ), which collects information on both vigorous and moderate-intensity activity in three settings: at work, traveling to and from places, and in recreational activities, as well as sedentary behavior (World Health Organization, 2012). From the GPAQ data, we calculated energy consumption based on Metabolic Equivalents (METs), where one MET is defined as the energy cost of sitting quietly and is equivalent to 1 kcal/kg/hour. Since caloric consumption is an estimated four times as high when moderately active and eight times as high when vigorously active, we calculated overall energy expenditure by assigning four METs to the time spent in moderate activities and eight METs to the time spent in vigorous activities (World Health Organization, 2012). We reported this estimated physical activity as MET-minutes per day. 2.4. Statistical Analysis Data were managed and analyzed using R version 4.3.3 (R Foundation for Statistical Computing) and RStudio 20 . Initially, 314 non-pregnant adult women who lived in the same household as an enrolled pregnant woman were included. For data cleaning, we removed those with missing BP values (n=6), those who reported taking high BP medicine (n=33), and those who had missing Pb and Cd values (n=3). The final dataset for analysis included 272 women with valid Pb and Cd measures. We calculated descriptive statistics for exposure, demographic, socioeconomic status and other potential confounders. We used a Directed Acyclic Graph (DAG) to help inform which covariates to investigate and which to consider for analysis (Supplemental Figure 1). Detailed exploratory data analysis assessed frequencies and mean (SD, median, Q1-Q3, min-max) of BP outcomes (systolic and diastolic), Pb and Cd exposures, and all other covariates. We used diagnostic plots of simple linear regression models for Pb and Cd measures and BP to see if the Pb and Cd measures needed to be natural log-transformed to meet the assumptions of linear regression. We highlighted covariates that lacked any variation in responses and considered creating new categories (binning) if necessary or dropping these covariates. We used covariates from the DAG and assessed associations with SBP and DBP and Pb and Cd in crude (i.e., unadjusted) linear regression models. We explored how these covariates were correlated with one another to assess for potentially strong correlations. We built multivariable linear regression models with women’s SBP and DBP as separate outcomes and Pb and Cd as separate exposures. We included a priori confounders (i.e., age) and potential confounders (SES and other indicators of SES, e.g., education, household assets, dietary diversity, and food insecurity). Since BMI may be a mediator (Supplemental Figure 1), we considered models with and without BMI as an adjusted variable in sensitivity analyses. Finally, we assessed effect modification in the adjusted linear regression models by adding an interaction term between the Pb and Cd exposure variables and age (median cutoff: <51 vs. ≥51 years) and by research site (Guatemala, Peru and Rwanda). 2.5. Ethical considerations The study protocol has been reviewed and approved by institutional review boards (IRBs) or Ethics Committees at Emory University (00089799), Johns Hopkins University (00007403), Sri Ramachandra Institute of Higher Education and Research (IEC-N1/16/JUL/54/49) and the Indian Council of Medical Research – Health Ministry Screening Committee (5/8/4-30/(Env)/Indo-US/2016-NCD-I), Universidad del Valle de Guatemala (146-08-2016) and Guatemalan Ministry of Health National Ethics Committee (11-2016), Asociación Benefica PRISMA (CE2981.17), the London School of Hygiene and Tropical Medicine (11664-5) and the Rwandan National Ethics Committee (No.357/RNEC/2018), and Washington University in St. Louis (201611159). The study has been registered with ClinicalTrials.gov (Identifier NCT02944682 ). 3. Results 3.1. Baseline characteristics The baseline characteristics of the participants are shown in Table 1 for those analyzed with Pb and Cd measures (n=272). The majority of metals data were from Guatemala (43%) and Peru (44%), with 13% from Rwanda. The average age of participants was 52.3 (SD 7.6) years. There was a notable prevalence of overweight and obesity (n=174, 65%) among the participants. The educational level was generally low with 77% (n=203) having no formal education or primary school incomplete ( Table 1 ). View this table: View inline View popup Table 1: Baseline characteristics among adult women with valid Pb and Cd measures, Guatemala, Peru, and Rwanda (N=272) Almost all participants had mobile phones (94%), while a half of them had radios (59%) and color tv (49%) and fewer had bicycles (31%) and a bank (30%) account. The data from this study suggested that a substantial proportion of the sample faced challenges related to both food insecurity and dietary diversity. Over half of the sample reported were food insecure with mild (36%) or moderate to severe (17%) levels. Additionally, dietary diversity was low for half the sample, indicating limited access to a variety of foods ( Table 1 ). The results also indicate that out of the total sample population, 16 individuals (6%) reported being exposed to secondhand tobacco smoke. Participants spent a substantial amount of physical exertion, as indicated by 1,086 average METs per day (SD 1,030), although the large standard deviation and the wide range of values (from 0 to 6,171 METs per day) reveal significant variation in exercise habits among individuals. The baseline levels of Pb and Cd as presented in Supplemental table1 and Supplemental figures 2 and 3 were; Guatemala: 117 samples, Mean = 2.02 (SD = 1.63), Median = 1.49, 25th percentile = 0.938, 75th percentile = 2.42, Min-Max = 0.08-8.72, Peru: 121 samples, Mean = 1.90 (SD = 1.90), Median = 1.19, 25th percentile = 0.880, 75th percentile = 1.99, Min-Max = 0.013-11.0 and Rwanda: 34 samples, Mean = 2.30 (SD = 2.27), Median = 1.47, 25th percentile = 0.937, 75th percentile = 2.79, Min-Max = 0.165-9.07 while for Cd; Guatemala: 117 samples, Mean = 0.996 (SD = 0.446), Median = 0.993, 25th percentile = 0.709, 75th percentile = 1.25, Min-Max = 0.116-2.23, Peru: 121 samples, Mean = 1.07 (SD = 0.462), Median = 1.05, 25th percentile = 0.775, 75th percentile = 1.42, Min-Max = 0.128-2.12 and Rwanda: 34 samples, Mean = 1.00 (SD = 0.434), Median = 1.03, 25th percentile = 0.728, 75th percentile = 1.30, Min-Max = 0.0921-1.95. The overall mean (SD) of SBP and DBP for all three research sites was 112.2 (14.5) mmHg and 67.3 (9.6) mmHg, respectively ( Table 2 ). The BP summary results ( Table 2 ) and boxplots of SBP and DBP by country ( Figures 2 and 3) indicated regional differences in BP among the study participants. Rwanda and Guatemala generally had higher BP levels compared to Peru. View this table: View inline View popup Download powerpoint Table 2: Summary of SBP and DBP among adult women with valid Pb and Cd measures at baseline visit per research site, HAPIN (Guatemala, Peru, Rwanda) N=272 3.2. Results from adjusted linear regression models Table 3 shows the adjusted associations between SBP and DBP and the concentrations of two metals, Pb and Cd. There was a statistically significant positive association between Pb exposure (log-transformed and not transformed) and SBP and DBB. The strongest association was observed as a 1-unit increase in log Pb value with an SBP increase by 2.36 mmHg (95% CI 0.51, 4.20). The adjusted associations between Cd exposure and SBP and DBP included the null value ( Table 3 ). Overall, results suggested that exposure to Pb, but not Cd, was associated with increases in both systolic and diastolic BPs in the studied sample ( Table 3 ). View this table: View inline View popup Download powerpoint Table 3. Primary results: Adjusted associations between outcomes of Systolic and Diastolic BP and exposures of Pb and Cd concentrations (K+ standardized) 1 . The sensitivity analysis ( Table 4 ) presents the adjusted associations between BP (both systolic and diastolic) and the concentrations of Pb and Cd, without an additional adjustment for BMI. The association between Pb exposure (log-transformed and untransformed) and SBP remained statistically significant after removing BMI (e.g., 2.32 mmHg (95% CI 0.43, 4.21 for log-transformed Pb). After removing BMI, there was still no statistically significant association between Cd exposure and SBP. The association between Pb exposure (log-transformed) and DBP also remained statistically significant. For a unit increase in the natural log of Pb concentration, DBP increased by 1.42 mmHg (95% CI 0.15, 2.70). After removing BMI, there remained no statistically significant association between Cd exposure and DBP. The sensitivity analyses confirmed that the associations observed between Pb exposure and increased BP were robust, regardless of the inclusion or exclusion of BMI. Cd exposure continued to show no significant association with BP changes in the adjusted models. View this table: View inline View popup Download powerpoint Table 4: Sensitivity Analysis Results: Adjusted associations between outcomes of Systolic and Diastolic BP and exposures of Pb and Cd concentrations (K+ standardized), excluding BMI 1 . Table 5 shows the effect modification results from the adjusted associations between outcomes of SBP and DBP and exposures of Pb and Cd concentrations. With interaction effects of exposure by age (median cutoff of <51 years and ≥51 years), and by research site (Guatemala, Peru, and Rwanda). Among women ≥51 years, there was an association with increased Pb per log-unit increase in Pb (3.41 mmHg (95% CI 0.79, 6.03). No other interaction models showed statistically significant interactions across age groups or countries, as all p-values for interaction were above 0.05 and 95% CIs included the null value. View this table: View inline View popup Table 5: Effect modification Models. Adjusted associations between outcomes of Systolic and Diastolic BP and exposures of Pb and Cd concentrations (K+ standardized), interactions with age and research site 4. Discussion Assessing metals’ exposure on SBP and DBP can provide insights into the broader implications of environmental health risks’ impacts on cardiovascular disease and inform public health strategies. A persistent public health concern in low- and middle-income countries is high BP, where cooking with solid biomass fuel is a prevalent practice. This produces dangerous levels of household air pollution, to which exposure can lead to significant morbidity and mortality, with air pollution accounting for nearly 1 in 6 deaths in children under 5 across Africa. Since women are most often the ones preparing meals on biomass cookstoves, they tend to have higher levels of exposure 19 . These results provided an insightful overview of the baseline characteristics of the participants, highlighting important socioeconomic, health, and lifestyle factors. These factors are likely interrelated and may exacerbate disparities in health outcomes indicating significant health and socioeconomic challenges among the participants, such as overweight/obesity (65%), food insecurity with 36% experiencing mild and 17% moderate, and low educational attainment (77%). While most participants owned mobile phones (94%), fewer had access to other assets like radios (59%), televisions (49%), bicycles (31%), or bank accounts (30%). These findings reflect varying levels of socioeconomic status and suggest limited access to diverse communication tools and financial services in some groups. These results also provided a comprehensive analysis of the associations between BP and exposure to Pb and Cd among adult women across Guatemala, Peru, and Rwanda, highlighting regional variations in BP levels among study participants, with Rwanda and Guatemala generally exhibiting higher SBP and DBP levels compared to Peru. In India, all participants that had valid blood pressure measurements at baseline and were largely normotensive (SBP <120 and DBP <80) (95%). The mean (SD) of SBP was 104.5 (9.1) mmHg and the mean (SD) of DBP was 61.5 (7.6) mmHg ( Table 3 ). Distributions of baseline SBP and DBP by study sites are visualized in Figure 1 and 2 . Thirteen pregnant women (2%) were considered as at hypertension stage 1, defined as SBP between 130 and 139 mmHg or DBP between 80 and 89 mmHg. Two individuals (<1% of the participants) were categorized as overly hypertensive, defined as SBP ≥140 mmHg or DBP ≥90 mmHg. The categorizations of normal blood pressure and of different stages of elevated blood pressure were not different between the two study sites 20 . Download figure Open in new tab Figure 1. Boxplots of SBP (mmHg) by research site among other women with valid Pb and Cd measures at baseline (Guatemala, Peru, and Rwanda, N=272). In this boxplot Rwanda and Guatemala have the highest median values (116.3 mmHg and 113.3 mmHg) respectively compared to Peru which has 106 mmHg (values also shown in Table 2 ). The box represents the interquartile range with the line at the median value, the whiskers extend to data points within 1.5*IQR and the outliers are the points beyond the whiskers. Download figure Open in new tab Figure 2: Boxplots of DBP (mmHg) by research site among other women with valid Pb and Cd measures at baseline (Guatemala, Peru, and Rwanda, N=272) which presents the median values of three countries/research sites. Rwanda had the highest median of 73mmHg followed by Guatemala and Peru with 68.3mmHg, 63.3mmHg respectively (values also shown in Table 2 ). The box represents the interquartile range with the line at the median value, the whiskers extend to data points within 1.5*IQR and the outliers are the points beyond the whiskers. Pb exposure, as indicated by the median levels, showed regional disparities, with Guatemala having the highest median Pb levels, followed by Peru and Rwanda. Cd exposure, on the other hand, exhibited similar median levels across the three research sites, indicating consistent central tendencies. Pb exposure (log-transformed) showed statistically significant positive associations with both SBP and DBP, with as much as a 2.36 mmHg and 1.42 mmHg increases observed in SBP and DBP per supplemental table 1 respectively. Cd exposure, however, did not show significant associations with BP changes. Sensitivity analyses, which excluded adjustment for BMI, confirmed the robustness of the associations between Pb exposure and BP changes. Even after excluding BMI, the positive associations remained statistically significant. Cd exposure continued to show no significant association with BP changes, even after removing BMI. Current literature suggests that high BP is a persistent public health concern in low- and middle-income countries, where environmental factors such as air pollution from biomass fuel use significantly contribute to morbidity and mortality. Previous studies have demonstrated that household air pollution, which is common in low-and-middle income countries due to the use of solid biomass fuels for cooking, disproportionately affects women, who often spend more time near cookstoves. This exposure contributes to adverse health outcomes, including cardiovascular diseases. Air pollution alone accounts for nearly one in six deaths among children under five years across Africa 21 , 22 , 23 . Prior research has also established a link between metal exposure and BP changes. For instance, a study in the United States that assessed associations of blood Pb, Cd, and mercury with resistant hypertension among adults in National Health and Nutrition Examination Survey, 1999–2018 showed that BP increased with higher concentrations of certain metals, including Pb (per 1μg/dL increase in blood Pb concentration, the proportion of resistant hypertension increased by 16% [adjusted odds ratio, 1.16; 95% confidence interval (CI) 1.01–1.32). This study adds to the existing body of knowledge by examining the associations between BP and metal exposure in diverse geographical regions, namely Guatemala, Peru, and Rwanda 24 , 25 .Positive associations were also observed between exposure to metals and age, BMI and DBP in a study conducted in Peru 26 . In Korea a study found significant associations of blood Cd and Pb with higher hypertension prevalence and there was a significant interaction between blood Cd and physical activity on hypertension risk 27 . These findings underscore the importance of understanding regional variations in BP levels and metal exposure for targeted public health interventions. The significant associations between Pb exposure and BP emphasize the need for policies and interventions aimed at reducing Pb exposure, especially in regions with high levels of exposure. Further research and monitoring are needed to better understand the mechanisms underlying the observed associations and to inform evidence-based interventions for preventing and managing hypertension and related cardiovascular diseases. Overall, these results contribute to our understanding of the complex relationships between environmental exposures, such as Pb and Cd, and cardiovascular health outcomes, highlighting the importance of multifaceted approaches to address public health challenges related to hypertension and metal exposure. 5. Conclusions Adjusted associations between SBP and DBP and Pb concentrations showed statistically significant positive associations, even after adjusting for various factors, including BMI. The sensitivity analysis further confirmed the robustness of the observed associations between Pb exposure and increased BP, even after removing BMI. In summary, these findings highlight potential implications for public health interventions and further research into the determinants of BP variations across different geographical contexts. Additionally, the associations between Pb exposure and increased BP warrant attention and may have implications for environmental and occupational health policies. Conflict of interests All authors declare no conflict of interest. Statement of data sharing Deidentified data associated with the paper will be deposited in Emory’s Dataverse data repository. A DOI for the data will be created, to allow citation with publication of the paper. Dataverse is widely accessible and provides long-term access to the public and to related research communities. Acknowledgements The HAPIN trial was funded by the U.S. National Institutes of Health (cooperative agreement 1UM1HL134590) in collaboration with the Bill & Melinda Gates Foundation [OPP1131279]. The investigators would like to thank the members of the advisory committee – Drs. Patrick Breysse, Donna Spiegelman, and Joel Kaufman - for their valuable insight and guidance throughout the implementation of the trial. We also wish to acknowledge all research staff and study participants for their dedication to and participation in this important trial. A multidisciplinary, independent Data and Safety Monitoring Board (DSMB) appointed by the National Heart, Lung, and Blood Institute (NHLBI) monitored the quality of the data and protected the safety of patients enrolled in the HAPIN trial. The DSMB consisted of: Catherine Karr (Chair), Nancy R. Cook, Stephen Hecht, Joseph Millum, Nalini Sathiakumar (deceased), Paul K. Whelton, and Gail Weinmann and Thomas Croxton (Executive Secretaries). Program Coordination: Gail Rodgers, Bill & Melinda Gates Foundation; Claudia L. Thompson, National Institute of Environmental Health Sciences; Mark J. Parascandola, National Cancer Institute; Marion Koso-Thomas, Eunice Kennedy Shriver National Institute of Child Health and Human Development; Joshua P. Rosenthal, Fogarty International Center; Concepcion R. Nierras, NIH Office of Strategic Coordination – The Common Fund; Katherine Kavounis, Dong-Yun Kim, Barry S. Schmetter (deceased), and Antonello Punturieri, NHLBI. This research represents the NIH’s contribution to the Global Alliance for Chronic Diseases (GACD) coordinated call for research on prevention and management of chronic lung diseases for 2016. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US National Institutes of Health or Department of Health and Human Services. References 1. ↵ Tchounwou PB , Yedjou CG , Patlolla AK , Sutton DJ . Heavy Metals Toxicity and the Environment . EXS . 2012 ; 101 : 133 . OpenUrl CrossRef PubMed 2. ↵ Witkowska D , Słowik J , Chilicka K . Heavy Metals and Human Health: Possible Exposure Pathways and the Competition for Protein Binding Sites . Molecules . 2021 Oct 7 ; 26 ( 19 ): 6060 . OpenUrl PubMed 3. ↵ Ramírez Ortega D , González Esquivel DF , Blanco Ayala T , Pineda B , Gómez Manzo S , Marcial Quino J , et al. Cognitive Impairment Induced by Lead Exposure during Lifespan: Mechanisms of Lead Neurotoxicity . Toxics . 2021 Jan 28 ; 9 ( 2 ): 23 . OpenUrl PubMed 4. ↵ Bakulski KM , Seo YA , Hickman RC , Brandt D , Vadari HS , Hu H , et al. Heavy Metals Exposure and Alzheimer’s Disease and Related Dementias . J Alzheimers Dis JAD . 2020 ; 76 ( 4 ): 1215 – 42 . OpenUrl PubMed 5. ↵ Collin MS , Venkatraman SK , Vijayakumar N , Kanimozhi V , Arbaaz SM , Stacey RGS , et al. Bioaccumulation of lead (Pb) and its effects on human: A review . J Hazard Mater Adv . 2022 Aug 1 ; 7 : 100094 . OpenUrl 6. ↵ Shezi B , Jafta N , Naidoo RN . Potential Health Risks of Indoor Particulate Matter Heavy Metals in Resource-Constrained Settings of South Africa . Atmosphere . 2024 Aug ; 15 ( 8 ): 911 . OpenUrl 7. ↵ Kwon JA , Kim B , Kim E , Kwon K . Interaction between blood cadmium and lead concentration and physical activity on hypertension from the Korean national health and nutrition examination survey in 2008–2013 . BMC Public Health . 2023 Apr 17 ; 23 ( 1 ): 703 . OpenUrl PubMed 8. ↵ Heavy Metal Poisoning and Cardiovascular Disease - PMC [Internet] . [cited 2024 Oct 22]. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3168898/ 9. ↵ Cardiovascular diseases (CVDs) [Internet] . [cited 2024 Oct 22]. Available from: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)?gad_source=1&gclid=Cj0KCQjwmt24BhDPARIsAJFYKk04SnDkAn_j8vcJ6a-3vhkeF3AL4mixrR4QUWlzVpy2Qk6L-7YIaRwaAl_CEALw_wcB 10. ↵ Vaziri ND . Mechanisms of lead-induced hypertension and cardiovascular disease . Am J Physiol - Heart Circ Physiol . 2008 Jun 20 ; 295 ( 2 ): H454 . OpenUrl 11. ↵ Hypertension and Aging - PMC [Internet] . [cited 2024 Oct 22]. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC4768730/ 12. ↵ Farzan SF , Howe CG , Chen Y , Gilbert-Diamond D , Cottingham KL , Jackson BP , et al. Prenatal Lead Exposure and Elevated Blood Pressure in Children . Environ Int . 2018 Oct 31 ; 121 (Pt 2 ): 1289 . OpenUrl PubMed 13. ↵ Shih YH , Howe CG , Scannell Bryan M , Shahriar M , Kibriya MG , Jasmine F , et al. Exposure to metal mixtures in relation to blood pressure among children 5–7 years old . Environ Epidemiol . 2021 Feb 11 ; 5 ( 2 ): e135 . OpenUrl 14. ↵ Han Z , Gong S , Tu Y , Lang C , Tang J , Wang T , et al. The Relationships Between Blood Pb Levels and Blood Pressure Among Lead-Exposed Workers in China: A Repeated-Measure Study . J Occup Environ Med . 2023 Dec ; 65 ( 12 ): e759 . OpenUrl PubMed 15. ↵ Design and Rationale of the HAPIN Study: A Multicountry Randomized Controlled Trial to Assess the Effect of Liquefied Petroleum Gas Stove and Continuous Fuel Distribution - PubMed [Internet] . [cited 2024 Oct 22]. Available from: https://pubmed.ncbi.nlm.nih.gov/32347766/ 16. ↵ Johnson MA , Steenland K , Piedrahita R , Clark ML , Pillarisetti A , Balakrishnan K , et al. Air Pollutant Exposure and Stove Use Assessment Methods for the Household Air Pollution Intervention Network (HAPIN) Trial . Environ Health Perspect . 128 ( 4 ): 047009 . 17. ↵ Pillarisetti A , Alnes LWH , Ye W , McCracken JP , Canuz E , Smith KR . Repeated assessment of PM2.5 in Guatemalan kitchens cooking with wood: Implications for measurement strategies . Atmos Environ . 2023 Feb 15 ; 295 : 119533 . OpenUrl 18. ↵ Fandiño-Del-Rio M , Kephart JL , Williams KN , Moulton LH , Steenland K , Checkley W , et al. Household air pollution exposure and associations with household characteristics among biomass cookstove users in Puno, Peru . Environ Res . 2020 Dec 1 ; 191 : 110028 . OpenUrl 19. ↵ nisr nisr. 5th POPULATION AND HOUSING CENSUS . 20. ↵ Index of /bin/windows/base/old/4.3.1 [Internet] . [cited 2024 Jun 9]. Available from: https://cran.r-project.org/bin/windows/base/old/4.3.1/ 21. ↵ Nicolaou L , Underhill L , Hossen S , Simkovich S , Thangavel G , Rosa G , et al. Cross-sectional analysis of the association between personal exposure to household air pollution and blood pressure in adult women: Evidence from the multi-country Household Air Pollution Intervention Network (HAPIN) trial . Environ Res . 2022 Nov 1 ; 214 : 114121 . OpenUrl 22. ↵ Wang X , Karvonen-Gutierrez CA , Herman WH , Mukherjee B , Harlow SD , Park SK . Urinary Heavy Metals and Longitudinal Changes in Blood Pressure in Midlife Women: The Study of Women’s Health Across the Nation . Hypertens Dallas Tex 1979 . 2021 Aug ; 78 ( 2 ): 543 – 51 . OpenUrl 23. ↵ Khoshakhlagh AH , Mohammadzadeh M , Gruszecka-Kosowska A , Oikonomou E . Burden of cardiovascular disease attributed to air pollution: a systematic review . Glob Health . 2024 May 3 ; 20 ( 1 ): 37 . OpenUrl 24. ↵ Effect of Household Air Pollution on Blood Pressure – A Review. [Internet] . [cited 2024 Dec 15]. Available from: https://imsear.searo.who.int/items/dc1ec750-37bc-44bb-9464-1b7872c9defa 25. ↵ Nicolaou L , Underhill L , Hossen S , Simkovich S , Thangavel G , Rosa G , et al. Cross-sectional analysis of the association between personal exposure to household air pollution and blood pressure in adult women: Evidence from the multi-country Household Air Pollution Intervention Network (HAPIN) trial . Environ Res . 2022 Nov ; 214 : 114121 . OpenUrl 26. ↵ Abba MS , Nduka CU , Anjorin S , Uthman OA . Household Air Pollution and High Blood Pressure: A Secondary Analysis of the 2016 Albania Demographic Health and Survey Dataset . Int J Environ Res Public Health . 2022 Feb 24 ; 19 ( 5 ): 2611 . OpenUrl PubMed 27. ↵ Chen H , Zou Y , Leng X , Huang F , Huang R , Wijayabahu A , et al. Associations of blood lead, cadmium, and mercury with resistant hypertension among adults in NHANES, 1999–2018 . Environ Health Prev Med . 28 : 66 . 28. Qu Y , Lv Y , Ji S , Ding L , Zhao F , Zhu Y , et al. Effect of exposures to mixtures of lead and various metals on hypertension, pre-hypertension, and blood pressure: A cross-sectional study from the China National Human Biomonitoring . Environ Pollut . 2022 Apr 15 ; 299 : 118864 . OpenUrl PubMed 29. Farzan SF , Howe CG , Chen Y , Gilbert-Diamond D , Cottingham KL , Jackson BP , et al. Prenatal lead exposure and elevated blood pressure in children . Environ Int . 2018 Dec 1 ; 121 : 1289 – 96 . OpenUrl PubMed View the discussion thread. Back to top Previous Next Posted January 22, 2025. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. 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