Association Between Household Air Pollution and Infant and Child Mortality in Myanmar: Evidence From The First Demographic and Health Survey

Background: Household air pollution (HAP) from solid fuel use (SFU) for cooking has been considered a public health threat, particularly for women and children in low and middle-income countries (LMICs), with limited evidence. This study was undertaken to investigate the effects of HAP on neonatal, infant, and under-ve child mortality in Myanmar. Methods: This cross-sectional study employed data from the Myanmar Demographic and Health Survey (MDHS), the rst nationally representative survey conducted in 2016. Data were collected from MDHS based on stratied two-stage cluster sampling design applied in urban and rural areas. The sample consists of 3249 under-ve children in the household with a 98% response rate. Exposure measures were HAP (coal and biomass) and level of exposure to HAP (no exposure, moderate and high exposure). The main outcomes were neonatal, infant, and under-ve child mortality reported by mothers presented in rates and risk ratios with 95% condence intervals, accounting for survey weight and cluster variation. Results: The prevalence of SFU was 79.0%. The neonatal, infant and under-ve child mortality rates were 26, 45, and 49 per 1,000 live births, respectively. The risks of infant (aRR 2.02; 95% CI: 1.01-4.05) and under-ve mortality (aRR 2.16; 95% CI: 1.07-4.36) mortality were higher among children from households with SFU compared to children from households using clean fuel. When applying an augmented measure of exposure to HAP by incorporating SFU and the kitchen's location, the likelihoods of infant and under-ve mortality were even higher among moderate and highly exposed children than unexposed children with similar trends. Neonatal mortality was not associated with either HAP exposure or levels of exposure to HAP. Conclusion: Infants and under-ve children are at higher risk of mortality from exposure to HAP.

ine cient combustion [7][8][9]. The amount of exposure to an individual in such settings has been measured to be much higher than the World Health Organization (WHO) guidelines and standards [10].
In LMICs, women and children are at higher risk of exposure to HAP [6,11,12] due to women's role in household chores, cooking, and caring for infants in most South Asian culture. Women spend about three to seven hours per day near the stove, sometimes carrying their infants for care and warmth during cooking that leads children exposed to biomass fuel at similar levels [3]. This exposure level increases in households with limited ventilation and poor design of the stove that do not have ues or hood to move out the smoke from living places [13].
The majority of households in Myanmar use solid fuels for cooking as easy access to biomass for domestic cooking, which is a convention [14]. Clean Cooking Alliance, Myanmar estimated that more than 95% of the rural and 88% of the urban population use solid fuels for cooking [14,15], which might be one of the contributing factors of more than 3,500 annual infant and children died from acute lower respiratory infections (ALRIs) and pneumonia in Myanmar. It could also be one of the reasons that Myanmar was unable to achieve the Millennium Development Goals (MDGs) (between 2000 and 2015) of reducing infant and child mortality [16]. Importantly, this indicates an important area to address for achieving the Sustainable Development Goals (SDGs) of reducing neonatal (12 per 10000 live birth) and infant (25 per 10000 live births) deaths between 2015 and 2030.
To our knowledge, no study has evaluated the effect of HAP from SFU on neonatal, infant, and under-ve mortality rates in Myanmar using nationally representative data. The rst Demographic Health Survey (DHS) in Myanmar was conducted in 2016 that provides an opportunity to examine the effect and extent of HAP on neonatal, infant, and under-ve child mortality.

Study Design and Setting
Given the focus on improving maternal and child health, the Myanmar Demographic and Health Survey (MDHS) 2016 was the rst nationally representative cross-sectional survey conducted in Myanmar. Data were collected from 12,885 women from the sampled households based on strati ed two-stage cluster sampling design from December 2015 to July 2016. Using the 2014 Myanmar census sampling units, 442 clusters (123 urban, 319 rural) were selected in the rst stage from 4,000 clusters based on the probability proportional to the size. In the second stage, 30 households from each selected cluster were selected in the rst stage by using systematic random sampling. The overall response rate was approximately 98%. The survey was funded by the United States Agency for International Development and implemented by the Ministry of Health and Sports, Myanmar, in coordination with the Millennium Development Goals. Technical support was provided by ICF international. Detail of the survey sampling procedure has been published in the MDHS report [17].

Characteristics of Participants
A total of 3,249 under-ve children was included in the nal analysis based on their retrospective birth histories after limiting to singleton births living with their mothers at the time of the survey and excluding children with missing information on SFU ( Figure 1) [17,18]. The inclusion criteria were: i) children born within ve years before the date of survey (only last child and singleton births were considered in case of multiple children in ve years); ii) most recent children with information of survival status (alive/death at the time of the survey); iii) children with the date of death if applicable; iv) children with complete information of household cooking fuels use [17].

Measures of Child Mortality Outcomes
We considered neonatal mortality (deaths occurred during the rst 28 days of life), infant mortality (deaths occurred during the rst one year (0-11 months) of life), and under-ve mortality (deaths occurred during the rst ve years (0-59 months) of life) as outcome variables [17,19,20].

Measures of HAP Exposure
The analysis was carried out for two exposure variables: Solid Fuel Use (clean fuel vs. solid fuel) and level of exposure to SFU induced HAP (non-exposure, moderate exposure, and high exposure). The MDHS collected information on the types of cooking fuels by asking women-what type of fuel does your household mainly use for cooking? Responses were coded as clean fuel =0 (if responses were electricity, liquid petroleum gas, and natural gas) and solid fuel =1 (if responses were coal, lignite, charcoal, wood, straw/shrubs, grass, and agricultural crop). Children's levels of exposure to HAP were generated from the women's responses to the place of cooking and the type of cooking fuel use. The responses were categorized as non-exposure =0 (if women reported not using solid fuel), moderate exposure =1 (if women reported using solid fuel, but in a separate building or outdoors), and high exposure =2 (if women reported using solid fuel inside the house).

Confounder Adjustment
Different sociodemographic factors contributing to neonatal, infant, and under-ve child mortality were included as confounders ( Figure 2). These were age at child deaths, child sex, parental education, interval of last two succeeding births, breastfeeding status, household wealth quintiles, urbanity, geographic regions, and seasons ( Figure 2). The birth interval variable was generated based on women's response to the birth date of the last two children and categorized by following the World Health Organization guidelines [17]. The wealth quintile was reconstructed from the women's household durable and nondurable assets (e.g., televisions, bicycles, sources of drinking water, sanitation facilities, and construction materials of houses) using principal components analysis, excluding the types of cooking fuels as this was the main exposure of interest [17,21]. Note: HAP is exposure, and child mortality is the outcome. The minimal and su cient adjustment set contains child age, child sex, breastfeeding status, maternal education, household wealth quintiles, urbanicity, geographic region, preceding birth interval, and season. This gure was constructed through DAG (http://www.dagitty.net/dags.htm).

Statistical Analysis
Descriptive statistics were reported as frequency and percentage to characterize the demographic pro le of the study sample. Differences in neonatal, infant, and under-ve child mortality across sociodemographic factors were presented using the chi-square test. The associations between exposure to HAP and child mortality outcomes were investigated using both univariable and multilevel Poisson regression models. As an additional analysis, effect modi cation by sex of the child was also tested for all models. The univariate models included only the exposure variable and the outcome variable. These associations were then progressively adjusted for potential confounders in the multivariable models, including child age, child sex, breasting status, maternal education, household wealth quintiles, urbanicity, geographic region, preceding birth interval, and season. However, birth weight and wasting were not adjusted in the models as they are likely to be on the causal pathway between exposure to HAP and mortality [22][23][24].
Furthermore, information on exact birth weight was unavailable for most of the children [17]. Multilevel Poisson models with robust error variance to minimize the overestimation of binary outcome were developed for complex survey design effects, adjusting clustering effects, individual and household characteristics of the children [18,21]. Results were reported as adjusted relative risks (aRRs) with 95% con dence intervals (CIs). All statistical tests were two-sided, and a p-value < 0·05 was considered statistically signi cant.

Results
Characteristics of sample, exposures, and outcomes are presented in Table 1. The mean (SD) age of the mothers was 31.1 (±6.0) years. The mean years of education were 4.4 (±3.5) years. The mean age of the child was 2.1 (±0.04) years, and 47.6% of the child were girls. More than three-quarters (77.8%) of the study households used solid fuels for cooking, of which 61.5% used solid fuels at the indoor cooking places. About two-thirds (64.5%) of the women reported indoor place of cooking. Nearly half of the children (47.7%) were highly exposed to HAP during the survey (  9) and under-ve child mortality (465.8, 95% CI: 325.3-611.9) per 1000 live births were very high amongst mothers who never breastfeed their child. Neonatal, infant, and under-ve child mortality were higher amongst richer and the richest compared with the poorest households. Infant and under-ve child mortality were higher among children whose mother had no education, resided in Shan, Chin, and Teninthayi regions, and were born in the short birth interval ( Table 2).
The unadjusted and adjusted associations between HAP and child mortality are presented in Table 3. The likelihood of infant mortality (2.02, aRR 95% CI: 1.01-4.05) and under-ve mortality (aRR 2.16, 95% CI: 1.07-4.36) were higher for children from households who used solid fuel for cooking compared with children from households who used clean fuel. The likelihoods were even higher when we considered the augmented measure of exposure to HAP. Compared with unexposed children, infant mortality risks were 1.94 (95% CI: 0.92-4.08) and 2.15 (95% CI: 1.04-4.43) times higher among moderately and highly HAP exposed children, respectively.
A similar higher likelihood of under-ve mortality was observed among children with moderate (aRR 2.11; 95% CI: 1.02-4.36) and high (aRR 2.25, 95% CI: 1.08-4.69) exposure to HAP than their counterparts. There was no association between neonatal mortality with HAP exposure and levels of exposure to HAP. As an additional analysis (not shown), we have statistically tested the effect modi cation of sex of children, but there were no signi cant sex differences in the mortality outcomes of under-ve children in Myanmar.

Discussion
The rst-ever nationally representative survey suggests that neonatal, infant, and under-ve child mortality rates were relatively higher in Myanmar compared with other Southeast Asian countries [16,19]. Most of the households were dependent on SFU for cooking and heating purposes, and almost half of the study children were highly exposed to HAP in Myanmar. The study demonstrates that HAP and moderate and high levels of exposure to HAP increased the risk of infant and under-ve child mortality, but not neonatal mortality in Myanmar.
Previous studies reported comparable results that HAP exposure from SFU increases the risk of infant and child mortality in LMICs [19,[25][26][27][28]. Evidence suggests that the combustion of SFU emits multiple pollutants such as ne particles, carbon monoxide, formaldehyde, and many more toxic chemicals, which increase the risk of mortality from ALRIs, asthma, and pneumonia among infants and young children exposed to these pollutants [3,7,8,21,[29][30][31][32][33][34]. Exposure to these toxic pollutants also increases the risk of stillbirth, low birth weight, and preterm birth, including acute and chronic health problems, all of which are considered leading causes of child mortality [19,28,35,36].
Previous studies suggest considering cooking place along with SFU to examine its effects on childmortality because cooking inside the house with solid fuels maximizes the concentrations of airborne toxic pollutants in the household and ambient air [19][20][21]37,38]. We employed an augmented SFU exposure measure combining SFU and cooking place following the previous study and found stronger effects of high exposure to HAP on infant and child mortality [21]. Consistent with our study, previous studies showed that children were exposed to higher concentration of pollutants from SFU because of high proximity to pollutants and spending much time in the kitchen during heating and cooking, which intensi es the risk of child mortality from ALRI, including other adverse health outcomes [21,25,29]. The plausible explanation is that young children are more susceptible to HAP-induced mortality than their older counterparts due to their underdeveloped epithelial linings of the lungs [21,39]. Furthermore, infants at their early age are often carried on their mothers' backs or placed to sleep or stand beside their mother when cooking, a common practice in Southeast Asian countries, including Myanmar [19,20,40,41].
In a healthy condition, infants and young children have higher respiration, and they breathe 50% more polluted air due to their narrower airways and large lung surface. Children have a weak immune system in their early years of life, making them vulnerable to HAP induced mortality, especially from ALRI [39,[42][43][44].
However, neonatal mortality was not signi cantly associated with SFU and exposure to HAP in our study, consistent with previous studies conducted in LMICs [25,45]. Several biological factors, such as low birth weight, prematurity, and complications associated with pregnancy and delivery, might be responsible for the null association between HAP and neonatal mortality [19,35,36]. Additionally, breastfeeding could work as a protective factor diminishing the effect of HAP on neonatal mortality. Moreover, neonates and mothers might live in a conducive environment right after delivery, as well as mothers usually stay away from any cooking activities during the neonatal period, which is a common cultural practice in Asia.
However, few studies claim that neonates are at higher risk of HAP induced mortality [28,41], which warrant further studies.
The main strength of the study was a nationally representative survey with a 98% response rate. The analysis of large-scale data with an appropriate statistical method and adjustments for potential confounders makes the study ndings more reliable for policymaking. However, the main weakness is that the temporal association between HAP exposure and child mortality outcomes cannot be established due to its cross-sectional nature. Second, the associations could be affected by unmeasured confounders and different health outcomes such as preterm birth, low birth weight, and other morbidity factors despite HAP exposure. Third, information related to the children's birth and death was reported by mothers that may introduce recall bias. However, it is unlikely that the mother would incorrectly report their children's birth and death. Fourth, there might be a source of exposure measurement error as we used two proxy measures such as SFU and combining SFU and cooking place to measure the associations between HAP exposures [21] and child mortality. However, this is the available robust and established measurement of HAP exposures because DHS does not objectively measure the level and duration of HAP exposures [20,21]. Further studies may include questions related to ventilation in the kitchen, duration of cooking, proximity to the kitchen, or heating areas to better measure children's exposure to HAP.

Conclusion
The study demonstrates that HAP is a signi cant risk factor for infant and under-ve child mortality but not neonatal mortality. Furthermore, both moderate and high levels of exposure to HAP, such as the combination of SFU and cooking inside the kitchen, increase the risk of infant and child mortality in Myanmar. Policymakers should take both short-term and long-term strategies through socioenvironmental pathways for addressing the problem of the higher rate of child mortality in Myanmar. To reduce child mortality, the government in Myanmar should implement national policies related to clean fuels, cookstoves, and green energy and reduce the level of exposure to HAP, which will ultimately help them meet several sustainable development goals. The ICF Institutional Review Board (IRB) and the Ministry of Health and Sports, Myanmar, approved the primary data collection survey protocol. We obtained the de-identi ed data from the DHS online archive. This is a public-use dataset. Informed consent was taken from each participant before the enrolment.  SD= standard deviation, CI= con dence interval, HAP= household air pollution