Prenatal and Postnatal Household Air Pollution Exposure and Infant Growth Trajectories: Evidence from a Rural Ghanaian Pregnancy Cohort

Ellen Boamah-Kaali, Darby W Jack, Kenneth A Ae-Ngibise, Ashlinn Quinn, Seyram Kaali, Kathryn Dubowski, Felix B Oppong, Blair J Wylie, Mohammed N Mujtaba, Carlos F Gould, Stephaney Gyaase, Steven Chillrud, Seth Owusu-Agyei, Patrick L Kinney, Kwaku Poku Asante, Alison G Lee, Ellen Boamah-Kaali, Darby W Jack, Kenneth A Ae-Ngibise, Ashlinn Quinn, Seyram Kaali, Kathryn Dubowski, Felix B Oppong, Blair J Wylie, Mohammed N Mujtaba, Carlos F Gould, Stephaney Gyaase, Steven Chillrud, Seth Owusu-Agyei, Patrick L Kinney, Kwaku Poku Asante, Alison G Lee

Abstract

Background: The exposure-response association between prenatal and postnatal household air pollution (HAP) and infant growth trajectories is unknown.

Objectives: To evaluate associations between prenatal and postnatal HAP exposure and stove interventions on growth trajectories over the first year of life.

Methods: The Ghana Randomized Air Pollution and Health Study enrolled n=1,414 pregnant women at ≤24wk gestation from Kintampo, Ghana, and randomized them to liquefied petroleum gas (LPG), improved biomass, or open fire (control) stoves. We quantified HAP exposure by repeated, personal prenatal and postnatal carbon monoxide (CO) and, in a subset, fine particulate matter [PM with an aerodynamic diameter of ≤2.5μm (PM2.5)] assessments. Length, weight, mid-upper arm circumference (MUAC) and head circumference (HC) were measured at birth, 3, 6, 9, and 12 months; weight-for-age, length-for-age (LAZ), and weight-for-length z (WLZ)-scores were calculated. For each anthropometric measure, we employed latent class growth analysis to generate growth trajectories over the first year of life and assigned each child to a trajectory group. We then employed ordinal logistic regression to determine associations between HAP exposures and growth trajectory assignments. Associations with stove intervention arm were also considered.

Results: Of the 1,306 live births, 1,144 had valid CO data and anthropometric variables measured at least once. Prenatal HAP exposure increased risk for lower length [CO odds ratio (OR)= 1.17, 95% CI: 1.01, 1.35 per 1-ppm increase; PM2.5 OR= 1.07, 95% CI: 1.02, 1.13 per 10-μg/m3 increase], lower LAZ z-score (CO OR= 1.15, 95% CI: 1.01, 1.32 per 1-ppm increase) and stunting (CO OR= 1.25, 95% CI: 1.08, 1.45) trajectories. Postnatal HAP exposure increased risk for smaller HC (CO OR= 1.09, 95% CI: 1.04, 1.13 per 1-ppm increase), smaller MUAC and lower WLZ-score (PM2.5 OR= 1.07, 95% CI: 1.00, 1.14 and OR= 1.09, 95% CI: 1.01, 1.19 per 10-μg/m3 increase, respectively) trajectories. Infants in the LPG arm had decreased odds of having smaller HC and MUAC trajectories as compared with those in the open fire stove arm (OR= 0.58, 95% CI: 0.37, 0.92 and OR= 0.45, 95% CI: 0.22, 0.90, respectively).

Discussion: Higher early life HAP exposure (during pregnancy and through the first year of life) was associated with poorer infant growth trajectories among children in rural Ghana. A cleaner-burning stove intervention may have improved some growth trajectories. https://doi.org/10.1289/EHP8109.

Trial registration: ClinicalTrials.gov NCT01335490.

Figures

Figure 1.
Figure 1.
CONSORT diagram of mother–infant dyads in the Ghana Randomized Air Pollution and Health Study. All mother–infant dyads with valid maternal prenatal and child postnatal CO had at least one valid anthropometric measure and were included in the growth trajectories construction. In the child follow-up section, the deaths of children at >7 d of age did not have any recorded fieldworker follow-up. Note: CO, carbon monoxide; LPG, liquified petroleum gas.
Figure 2.
Figure 2.
(A) Latent class growth trajectories for (a) weight, (b) length, (c) head circumference, and (d) MUAC. Weight, length, head circumference, and MUAC were measured at birth and at 3, 6, 9, and 12 months, and latent class growth analyses were employed to construct trajectories for each measurement. In general, trajectories appear distinct at birth although differences in slope are visualized through 6 months of life. (B) Latent class growth trajectories for (a) WAZ, (b) LAZ, and (c) WLZ calculated from 3 months of age using the 2006 WHO child growth standards. z-Score trajectories suggest that trajectories of wasting (WLZ<−2), stunting (LAZ<−2), and underweight (WAZ<−2) are largely present at 3 months of age and persist through 12 months of age. Note: LAZ, length-for-age z-score; MUAC, mid-upper arm circumference; WAZ, weight-for-age z-score; WLZ, weight-for-length z-score; WHO, World Health Organization.

References

    1. Akombi BJ, Agho KE, Renzaho AM, Hall JJ, Merom DR. 2019. Trends in socioeconomic inequalities in child undernutrition: evidence from Nigeria Demographic and Health Survey (2003–2013). PLoS One 14(2):e0211883, PMID: , 10.1371/journal.pone.0211883.
    1. Alexander DA, Northcross A, Karrison T, Morhasson-Bello O, Wilson N, Atalabi OM, et al. . 2018. Pregnancy outcomes and ethanol cook stove intervention: a randomized-controlled trial in Ibadan, Nigeria. Environ Int 111:152–163, PMID: , 10.1016/j.envint.2017.11.021.
    1. Amegah AK, Quansah R, Jaakkola JJ. 2014. Household air pollution from solid fuel use and risk of adverse pregnancy outcomes: a systematic review and meta-analysis of the empirical evidence. PLoS One 9(12):e113920, PMID: , 10.1371/journal.pone.0113920.
    1. Balakrishnan K, Ghosh S, Thangavel G, Sambandam S, Mukhopadhyay K, Puttaswamy N, et al. . 2018. Exposures to fine particulate matter (PM2.5) and birthweight in a rural-urban, mother-child cohort in Tamil Nadu, India. Environ Res 161:524–531, PMID: , 10.1016/j.envres.2017.11.050.
    1. Berlin KS, Parra GR, Williams NA. 2014. An introduction to latent variable mixture modeling (part 2): longitudinal latent class growth analysis and growth mixture models. J Pediatr Psychol 39(2):188–203, PMID: , 10.1093/jpepsy/jst085.
    1. Black RE, Victora CG, Walker SP, Bhutta ZA, Christian P, de Onis M, et al. . 2013. Maternal and child undernutrition and overweight in low-income and middle-income countries. Lancet 382(9890):427–451, PMID: , 10.1016/S0140-6736(13)60937-X.
    1. Block ML, Calderón-Garcidueñas L. 2009. Air pollution: mechanisms of neuroinflammation and CNS disease. Trends Neurosci 32(9):506–516, PMID: , 10.1016/j.tins.2009.05.009.
    1. Boamah EA, Asante K, Ae-Ngibise K, Kinney PL, Jack DW, Manu G, et al. . 2014. Gestational age assessment in the Ghana Randomized Air Pollution and Health Study (GRAPHS): ultrasound capacity building, fetal biometry protocol development, and ongoing quality control. JMIR Res Protoc 3(4):e77, PMID: , 10.2196/resprot.3797.
    1. Briend A, Khara T, Dolan C. 2015. Wasting and stunting—similarities and differences: policy and programmatic implications. Food Nutr Bull 36(1 suppl):S15–S23, PMID: , 10.1177/15648265150361S103.
    1. Calderón-Garcidueñas L, Mora-Tiscareño A, Ontiveros E, Gómez-Garza G, Barragán-Mejía G, Broadway J, et al. . 2008. Air pollution, cognitive deficits and brain abnormalities: a pilot study with children and dogs. Brain Cogn 68(2):117–127, PMID: , 10.1016/j.bandc.2008.04.008.
    1. Chillrud SN, Ae-Ngibise KA, Gould CF, Owusu-Agyei S, Mujtaba M, Manu G, et al. . 2021. The effect of clean cooking interventions on mother and child personal exposure to air pollution: results from the Ghana Randomized Air Pollution and Health Study (GRAPHS). J Expo Sci Environ Epidemiol 31(4):683–698, PMID: , 10.1038/s41370-021-00309-5.
    1. Christian P, Mullany LC, Hurley KM, Katz J, Black RE. 2015. Nutrition and maternal, neonatal, and child health. Semin Perinatol 39(5):361–372, PMID: , 10.1053/j.semperi.2015.06.009.
    1. Clark ML, Peel JL, Balakrishnan K, Breysse PN, Chillrud SN, Naeher LP, et al. . 2013. Health and household air pollution from solid fuel use: the need for improved exposure assessment. Environ Health Perspect 121(10):1120–1128, PMID: , 10.1289/ehp.1206429.
    1. Clemente DBP, Casas M, Janssen BG, Lertxundi A, Santa-Marina L, Iñiguez C, et al. . 2017. Prenatal ambient air pollution exposure, infant growth and placental mitochondrial DNA content in the INMA birth cohort. Environ Res 157:96–102, PMID: , 10.1016/j.envres.2017.05.018.
    1. Clifford A, Lang L, Chen R, Anstey KJ, Seaton A. 2016. Exposure to air pollution and cognitive functioning across the life course—a systematic literature review. Environ Res 147:383–398, PMID: , 10.1016/j.envres.2016.01.018.
    1. Danaei G, Andrews KG, Sudfeld CR, Fink G, McCoy DC, Peet E, et al. . 2016. Risk factors for childhood stunting in 137 developing countries: a comparative risk assessment analysis at global, regional, and country levels. PLoS Med 13(11):e1002164, PMID: , 10.1371/journal.pmed.1002164.
    1. Fekadu Y, Mesfin A, Haile D, Stoecker BJ. 2015. Factors associated with nutritional status of infants and young children in Somali Region, Ethiopia: a cross-sectional study. BMC Public Health 15:846, PMID: , 10.1186/s12889-015-2190-7.
    1. Fernández-Real JM, Ricart W. 1999. Insulin resistance and inflammation in an evolutionary perspective: the contribution of cytokine genotype/phenotype to thriftiness. Diabetologia 42(11):1367–1374, PMID: , 10.1007/s001250051451.
    1. Freemark M. 2015. Metabolomics in nutrition research: biomarkers predicting mortality in children with severe acute malnutrition. Food Nutr Bull 36(1 suppl):S88–S92, PMID: , 10.1177/15648265150361S114.
    1. Garenne M, Willie D, Maire B, Fontaine O, Eeckels R, Briend A, et al. . 2009. Incidence and duration of severe wasting in two African populations. Public Health Nutr 12(11):1974–1982, PMID: , 10.1017/S1368980009004972.
    1. GBD 2015 Risk Factors Collaborators. 2016. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet 388(10053):1659–1724, PMID: , 10.1016/S0140-6736(16)31679-8.
    1. GBD 2019 Risk Factors Collaborators. 2020. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396(10258):1223–1249, PMID: , 10.1016/S0140-6736(20)30752-2.
    1. Ghods E, Kreissl A, Brandstetter S, Fuiko R, Widhalm K. 2011. Head circumference catch-up growth among preterm very low birth weight infants: effect on neurodevelopmental outcome. J Perinat Med 39(5):579–586, PMID: , 10.1515/jpm.2011.049.
    1. Greenland S, Pearl J, Robins JM. 1999. Causal diagrams for epidemiologic research. Epidemiology 10:37–48, PMID: , 10.1097/00001648-199901000-00008.
    1. Gunnsteinsson S, Labrique AB, West KP Jr, Christian P, Mehra S, Shamim AA, et al. . 2010. Constructing indices of rural living standards in Northwestern Bangladesh. J Health Popul Nutr 28(5):509–519, PMID: , 10.3329/jhpn.v28i5.61600.
    1. Harrell FE. 2001. Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis. New York, NY: Springer-Verlag.
    1. Huang YJ, Boushey HA. 2015. The microbiome in asthma. J Allergy Clin Immunol 135(1):25–30, PMID: , 10.1016/j.jaci.2014.11.011.
    1. Isanaka S, Grais RF, Briend A, Checchi F. 2011. Estimates of the duration of untreated acute malnutrition in children from Niger. Am J Epidemiol 173(8):932–940, PMID: , 10.1093/aje/kwq436.
    1. Islam S, Rana MJ, Mohanty SK. 2021. Cooking, smoking, and stunting: effect of household air pollution sources on childhood growth in India. Indoor Air 31(1):229–249, PMID: , 10.1111/ina.12730.
    1. Jack DW, Ae-Ngibise KA, Gould CF, Boamah-Kaali E, Lee AG, Mujtaba MN, et al. . 2021. A cluster randomised trial of cookstove interventions to improve infant health in Ghana. BMJ Glob Health 6(8):e005599, PMID: , 10.1136/bmjgh-2021-005599.
    1. Jack DW, Asante KP, Wylie BJ, Chillrud SN, Whyatt RM, Ae-Ngibise KA, et al. . 2015. Ghana Randomized Air Pollution and Health Study (GRAPHS: study protocol for a randomized controlled trial. Trials 16:420, PMID: , 10.1186/s13063-015-0930-8.
    1. Jetter J, Ebersviller S. 2016. Test Report. BioLite HomeStove with Wood Fuel: Air Pollutant Emissions and Fuel Efficiency. EPA/625/R-16/001. Washington, DC: U.S. Environmental Protection Agency. [accessed 8 March 2021].
    1. Jung T, Wickrama KAS. 2008. An introduction to latent class growth analysis and growth mixture modeling. Soc Personal Psychol Compass 2(1):302–317, 10.1111/j.1751-9004.2007.00054.x.
    1. Kaali S, Jack D, Delimini R, Hu L, Burkart K, Opoku-Mensah J, et al. . 2018. Prenatal household air pollution alters cord blood mononuclear cell mitochondrial DNA copy number: sex-specific associations. Int J Environ Res Public Health 16(1):26, PMID: , 10.3390/ijerph16010026.
    1. Kaali S, Jack D, Opoku-Mensah J, Bloomquist T, Aanaro J, Quinn A, et al. . 2021. Prenatal household air pollution exposure, cord blood mononuclear cell telomere length and age four blood pressure: evidence from a Ghanaian pregnancy cohort. Toxics 9(7):169, PMID: , 10.3390/toxics9070169.
    1. Kinney PL, Asante K-P, Lee AG, Ae-Ngibise KA, Burkart K, Boamah-Kaali E, et al. . 2021. Prenatal and postnatal household air pollution exposures and pneumonia risk: evidence from the Ghana Randomized Air Pollution and Health Study. Chest 160(5):1634–1644, PMID: , 10.1016/j.chest.2021.06.080.
    1. Kish L, Hotte N, Kaplan GG, Vincent R, Tso R, Gänzle M, et al. . 2013. Environmental particulate matter induces murine intestinal inflammatory responses and alters the gut microbiome. PLoS One 8(4):e62220, PMID: , 10.1371/journal.pone.0062220.
    1. Lee AG, Kaali S, Quinn A, Delimini R, Burkart K, Opoku-Mensah J, et al. . 2019. Prenatal household air pollution is associated with impaired infant lung function with sex-specific effects. Evidence from GRAPHS, a cluster randomized cookstove intervention trial. Am J Respir Crit Care Med 199(6):738–746, PMID: , 10.1164/rccm.201804-0694OC.
    1. Lee-Sarwar KA, Kelly RS, Lasky-Su J, Zeiger RS, O’Connor GT, Sandel MT, et al. . 2019. Integrative analysis of the intestinal metabolome of childhood asthma. J Allergy Clin Immunol 144(2):442–454, PMID: , 10.1016/j.jaci.2019.02.032.
    1. Liang W, Wang B, Shen G, Cao S, Mcswain B, Qin N, et al. . 2020. Association of solid fuel use with risk of stunting in children living in China. Indoor Air 30(2):264–274, PMID: , 10.1111/ina.12627.
    1. McCracken JP, Schwartz J, Bruce N, Mittleman M, Ryan LM, Smith KR. 2009. Combining individual- and group-level exposure information: child carbon monoxide in the Guatemala woodstove randomized control trial. Epidemiology 20(1):127–136, PMID: , 10.1097/EDE.0b013e31818ef327.
    1. Mishra V, Retherford RD. 2007. Does biofuel smoke contribute to anaemia and stunting in early childhood? Int J Epidemiol 36(1):117–129, PMID: , 10.1093/ije/dyl234.
    1. Mutlu EA, Comba IY, Cho T, Engen PA, Yazici C, Soberanes S, et al. . 2018. Inhalational exposure to particulate matter air pollution alters the composition of the gut microbiome. Environ Pollut 240:817–830, PMID: , 10.1016/j.envpol.2018.04.130.
    1. Mutlu EA, Engen PA, Soberanes S, Urich D, Forsyth CB, Nigdelioglu R, et al. . 2011. Particulate matter air pollution causes oxidant-mediated increase in gut permeability in mice. Part Fibre Toxicol 8:19, PMID: , 10.1186/1743-8977-8-19.
    1. Nagin DS, Odgers CL. 2010. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol 6:109–138, PMID: , 10.1146/annurev.clinpsy.121208.131413.
    1. Nylund KL, Asparouhov T, Muthén BO. 2007. Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Modeling 14(4):535–569, 10.1080/10705510701575396.
    1. Olofin I, McDonald CM, Ezzati M, Flaxman S, Black RE, Fawzi WW, et al. . 2013. Associations of suboptimal growth with all-cause and cause-specific mortality in children under five years: a pooled analysis of ten prospective studies. PLoS One 8(5):e64636, PMID: , 10.1371/journal.pone.0064636.
    1. Oluwole O, Arinola GO, Ana GR, Wiskel T, Huo D, Olopade OI, et al. . 2013. Relationship between household air pollution from biomass smoke exposure, and pulmonary dysfunction, oxidant-antioxidant imbalance and systemic inflammation in rural women and children in Nigeria. Glob J Health Sci 5(4):28–38, PMID: , 10.5539/gjhs.v5n4p28.
    1. Pelletier DL. 1994. The relationship between child anthropometry and mortality in developing countries: implications for policy, programs and future research. J Nutr 124(10 suppl):2047S–2081S, PMID: , 10.1093/jn/124.suppl_10.2047S.
    1. Pun VC, Dowling R, Mehta S. 2021. Ambient and household air pollution on early-life determinants of stunting—a systematic review and meta-analysis. Environ Sci Pollut Res Int 28(21):26404–26412, PMID: , 10.1007/s11356-021-13719-7.
    1. Quinn AK, Adjei IA, Ae-Ngibise KA, Agyei O, Boamah-Kaali EA, Burkart K, et al. . 2021. Prenatal household air pollutant exposure is associated with reduced size and gestational age at birth among a cohort of Ghanaian infants. Environ Int 155:106659, PMID: , 10.1016/j.envint.2021.106659.
    1. Räikkönen K, Forsén T, Henriksson M, Kajantie E, Heinonen K, Pesonen A-K, et al. . 2009. Growth trajectories and intellectual abilities in young adulthood: the Helsinki Birth Cohort Study. Am J Epidemiol 170(4):447–455, PMID: , 10.1093/aje/kwp132.
    1. Rosofsky AS, Fabian MP, Ettinger de Cuba S, Sandel M, Coleman S, Levy JI, et al. . 2020. Prenatal ambient particulate matter exposure and longitudinal weight growth trajectories in early childhood. Int J Environ Res Public Health 17(4):1444, PMID: , 10.3390/ijerph17041444.
    1. Saenen ND, Martens DS, Neven KY, Alfano R, Bové H, Janssen BG, et al. . 2019. Air pollution-induced placental alterations: an interplay of oxidative stress, epigenetics, and the aging phenotype? Clin Epigenetics 11(1):124, PMID: , 10.1186/s13148-019-0688-z.
    1. Sinharoy SS, Clasen T, Martorell R. 2020. Air pollution and stunting: a missing link? Lancet Glob Health 8(4):e472–e475, PMID: , 10.1016/S2214-109X(20)30063-2.
    1. Smith KR, McCracken JP, Weber MW, Hubbard A, Jenny A, Thompson LM, et al. . 2011. Effect of reduction in household air pollution on childhood pneumonia in Guatemala (RESPIRE): a randomised controlled trial. Lancet 378(9804):1717–1726, PMID: , 10.1016/S0140-6736(11)60921-5.
    1. Thompson LM, Bruce N, Eskenazi B, Diaz A, Pope D, Smith KR. 2011. Impact of reduced maternal exposures to wood smoke from an introduced chimney stove on newborn birth weight in rural Guatemala. Environ Health Perspect 119(10):1489–1494, PMID: , 10.1289/ehp.1002928.
    1. Tielsch JM, Katz J, Thulasiraj RD, Coles CL, Sheeladevi S, Yanik EL, et al. . 2009. Exposure to indoor biomass fuel and tobacco smoke and risk of adverse reproductive outcomes, mortality, respiratory morbidity and growth among newborn infants in south India. Int J Epidemiol 38(5):1351–1363, PMID: , 10.1093/ije/dyp286.
    1. van den Hooven EH, Pierik FH, de Kluizenaar Y, Willemsen SP, Hofman A, van Ratingen SW, et al. . 2012. Air pollution exposure during pregnancy, ultrasound measures of fetal growth, and adverse birth outcomes: a prospective cohort study. Environ Health Perspect 120(1):150–156, PMID: , 10.1289/ehp.1003316.
    1. WHO (World Health Organization). 2006. WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age: Methods and Development. Geneva, Switzerland: World Health Organization, Department of Nutrition for Health and Development. [accessed 9 November 2021].
    1. Williams KN, Kephart JL, Fandiño-Del-Rio M, Simkovich SM, Koehler K, Harvey SA, et al. . 2020. Exploring the impact of a liquefied petroleum gas intervention on time use in rural Peru: a mixed methods study on perceptions, use, and implications of time savings. Environ Int 145:105932, PMID: , 10.1016/j.envint.2020.105932.
    1. World Bank. 2020. Databank: World Development Indicators. [accessed 7 December 7 2020].
    1. Wylie BJ, Kishashu Y, Matechi E, Zhou Z, Coull B, Abioye AI, et al. . 2017a. Maternal exposure to carbon monoxide and fine particulate matter during pregnancy in an urban Tanzanian cohort. Indoor Air 27(1):136–146, PMID: , 10.1111/ina.12289.
    1. Wylie BJ, Matechi E, Kishashu Y, Fawzi W, Premji Z, Coull BA, et al. . 2017b. Placental pathology associated with household air pollution in a cohort of pregnant women from Dar Es Salaam, Tanzania. Environ Health Perspect 125(1):134–140, PMID: , 10.1289/EHP256.
    1. Zhang T, Chillrud SN, Ji J, Chen Y, Pitiranggon M, Li W, et al. . 2017. Comparison of PM2.5 exposure in hazy and non-hazy days in Nanjing, China. Aerosol Air Qual Res 17(9):2235–2246, PMID: , 10.4209/aaqr.2016.07.0301.
    1. Zheng T, Zhang J, Sommer K, Bassig BA, Zhang X, Braun J, et al. . 2016. Effects of environmental exposures on fetal and childhood growth trajectories. Ann Glob Health 82(1):41–99, PMID: , 10.1016/j.aogh.2016.01.008.

Source: PubMed

3
Předplatit