Main findings
In our cross-sectional study of the association of multiple sources of smoke exposure with the risk of anemia/HB level, the participants' mean hemoglobin level (HB) was 12.6 ± 2.1 g/dL and their anemia prevalence were 49.1%. We found an exposure-response relationships of number of different types of waste openly burnt simultaneously, fuel stacking, and frequency of garbage burning by a neighbour with anemia risk and HB level. An exposure-response relationships was also observed of current smoking behaviour, exposure to SHS frequency of cooking, location of cooking, and duration of cooking with HB. Living close to a major road or involvement in fish smoking, and any smoke/fumes exposure indicator in the neighbourhood are also associated with HB level.
Methodological Validity
Our study has a few advantages. To the best of our knowledge, this is the first study to investigate the relationship between various sources of smoke commonly encountered in urban informal settlements and the risk of anemia and HB level. Confounding factors were determined based on their statistical significance (p < 0.05) in relation to anemia/HB and were consistent with the literature [3–6]. Data on HB/anemia were collected objectively by phlebotomists with more than ten years of laboratory experience. Participants were interviewed prior to blood sampling, and their anemia status had no bearing on their responses to the questionnaire questions. Again, the phlebotomists were unaware of the participants' exposure status. As a result, information bias related to anemia/smoke exposure was highly unlikely. When interpreting the findings of this study, a few limitations must be considered. The research was conducted during the peak of the COVID-19 infection when house-to-house visits were restricted. As a result, our planned hospital-based study may result in selection bias. It is important to note that patients attending the hospital that day were unaware of the study and that individuals experiencing severe anaemic symptoms attending the hospitals could do so at random, reducing the effect estimate to null. Furthermore, the cross-sectional design eliminates any temporality. Nonetheless, an exposure-response relationship between our smoke/fume exposure indicators was observed, implying plausible causal relationships. Our investigation was hampered by a lack of data on particulate matter and/or carbon monoxide concentrations. We were limited by COVID-19 infection restrictions, particularly in informal urban settlements where cases were on the rise during data collection. However, in contrast to the more time-consuming and capital-intensive pollutant assessment [7], the use of several factors influencing household air pollution exposure is an alternative assessment approach [7]. We also did not account for other important confounders like nutrition, wealth index, maternal history of anemia, and chronic diseases because we did not collect data on them. Some of our analyses have insufficient power to detect any association, increasing the margin of error and compromising the precision of our parameter estimates.
Comparison of our findings with previous studies
Our systematic search of the literature yielded 16 studies linking PM/air pollution/biomass fuel smoke to anemia risk/HB level in developing countries, plus three more from China, South Korea, and the USA. The risk of anemia has been documented in some, but not all, previously published studies. Mishra and Retherford [19] analysed secondary data from the 1998-99 national family health survey (NHFS-2) in India, which collected information on height, weight, and blood hemoglobin of 29 768 children aged 0–35 months from 92 486 households. Mishra and Retherford [17] categorized households into two groups depending on whether they used clean fuel exclusively (i.e., LPG or kerosene or electricity), mixed fuel (i.e., users of both clean and dirty fuel), or biomass fuel alone. After adjusting for potential confounders, users of biomass fuel alone (relative risk ratio (RRR) = 1.84, 95% CI 1.44–2.36 = 1.88) and users of mixed fuel (RRR = 1.44, 1.22–1.94) showed a higher risk of moderate-to-severe anemia than users of clean fuel. In a follow-up study conducted, Baranwal et al. [5] examined the NHFS-3 and, with a larger sample size (i.e., 52,868), demonstrated that using clean fuel (LPG, electricity, or biogas) significantly lowers the risk of anemia in children under the age of five yeras. Studies of expectant mothers [3, 5], preschool aged-children [16, 28], and housewives in South Korea [15], as well as secondary data analysis of the Demographic and Health Surveys for 29 countries [16], have confirmed these findings. Machisa et al. [18], on the other hand, were unable to replicate the same findings in Swazi pre-schoolers. Mean HB levels were not related to smoke exposure among communities living in the Guatemalan highlands [22]. In contrast to the findings of other studies (such as [18, 22]), but in line with prior findings (such as [19]), our investigation on fuel stacking found an exposure-response association with anemia risk. Our definition of biomass fuel smoke exposure agreed with Mishra and Retherford's [19] definition. The authors of Baranwal et al. [5] and Amadu et al. [2] employed both clean and unclean cooking, nevertheless. LPG, biogas, kerosene, and electricity were deemed to be “clean” for cooking, whereas coal, charcoal, and other filthy fuels were deemed to be “unclean”. While Kyu et al. 16] employed moderate and high exposure to biomass fuel smoke, there was no clear explanation of this term. Fuel stacking, a common practice in households in developing countries, was not considered by any of the latter definitions, which may have biased their observed effect. In contrast with populations in India's young children [5], sub-Saharan Africa's adult populations [2] and Ghana's central and Volta regions [4, 9], our informal settlement population experienced an increased prevalence of anemia. Only indoor sources such smoke from burning biomass fuel were considered in prior studies that related the risk of anemia to smoke exposure. Armo-Annor et al. [4] discovered that women who smoke fish outdoors in partially enclosed smokehouses have an increased risk of anemia (1.8, 1.1-3.0). Exposure to ambient PM2.5 levels among Peruvian children was significantly associated with decreased average hemoglobin levels and moderate/severe anemia [20]. These results were validated in an adult Chinese population exposed to ambient PM10, PM2.5, PM1, and NO2 as well as in an adult American population [10]. The current study identified several smoke sources, including those in households, neighbourhoods, and workplaces, which are characteristic in informal settlements. In contrast to our findings on the frequency of cooking, Armo-Annor et al. [4] observed no association between the number of days spent smoking fish and the risk of anemia. Unlike fish smoking, cooking is an everyday practice performed by households and may reflect intensity of smoke exposure. Cooking in an enclosed environment was associated with reduced average HB levels than cooking in an open area or outdoors, but the effect estimate was inconsistent.
Additionally, we demonstrated for the first time an association between risk of anemia/mean HB levels and garbage burning in the household and in the neighbourhood. Our research also indicated a link between the risk of anemia/mean HB levels and living near a busy road. The latter result is in line with earlier research on outdoor particulate matter exposure [20]. Prior studies have frequently concentrated on populations in rural communities, the general population, or urban populations. This study is the first to provide evidence of the association between various sources of smoke exposure and the risk of anemia in informal settlements. Our findings have significant public health implications for those living in informal settlements, where exposure to smoke from varieties of community sources is a common scene. It is anticipated that by 2050, the number of people living in informal settlements will double [26], along with the sources and sinks of air pollution. Governments in developing nations should put in place pragmatic measures to control smoke emissions from different sources to protect human health and well-being.