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The DHS Working Papers series is an unreviewed and unedited prepublication series of papers reporting 

on research in progress based on Demographic and Health Surveys (DHS) data. Funding for this research 

was provided by the National Institute of Child Health and Human Development (NICHD) (# 1 R03 

HD043929-01). Additional support was provided by the United States Agency for International 

Development (USAID) through the MEASURE DHS project (# GPO-C-00-03-00002-00). Views 

expressed are those of the authors and do not necessarily reflect the views of NICHD, USAID, the United 

States Government, or the organizations with which the authors are affiliated. 

MEASURE DHS assists countries worldwide in the collection and use of data to 

monitor and evaluate population, health, and nutrition programs. Additional 

information about the MEASURE DHS project can be obtained by contacting ORC 

Macro, Demographic and Health Research Division, 11785 Beltsville Drive, Suite 300, 

Calverton, MD 20705 (telephone: 301-572-0200; fax: 301-572-0999; e-mail: 

reports@orcmacro.com; internet: www.measuredhs.com). 
Does biofuel smoke contribute to anemia and stunting in early childhood?

Vinod Mishra1,2 and Robert D. Retherford2

March 2006 

Institutional affiliations: 1

ORC Macro, Calverton, MD; 2East-West Center, Honolulu, HI 

Corresponding author: Vinod Mishra, Demographic and Health Research Division, ORC 

Macro,11785 Beltsville Drive, Suite 300, Calverton, MD 20705. Phone: 301-572-0220, Fax: 

301-572-0999, Email: vinod.mishra@orcmacro.com

iii

ABSTRACT 

Background: Reliance on biomass fuels for cooking and heating exposes many women and 

young children in developing countries to high levels of air pollution indoors. Exposure to 

biomass smoke has been linked to reduced birth weight, acute respiratory infections, and 

childhood mortality. This study examines the association between household use of biofuels 

(wood, dung, and crop residues) for cooking and heating and prevalence of anemia and stunting 

in children.

Methods: Data are from a 1998–99 national family health survey in India, which measured 

height, weight, and blood hemoglobin of 29,768 children aged 0–35 months in 92,486 

households. Multinomial logistic regression is used to estimate the effects of biofuel use on 

prevalence of anemia and stunting, controlling for ETS, recent episodes of illness, maternal 

education and nutrition, and other potentially confounding factors.

Results: Analysis shows that prevalence of moderate-to-severe anemia was significantly higher 

among children in households using biofuels than among children in households using cleaner 

fuels (RRR=1.58; 95% CI: 1.28, 1.94), independent of other factors. Prevalence of severe 

stunting was also significantly higher among children in biofuel-using households (RRR=1.84; 

95% CI: 1.44, 2.36). Effects on mild anemia and moderate stunting were smaller, but positive 

and statistically significant. Effects of ETS on anemia and stunting were small and not 

significant.

Conclusions: The study provides a first evidence of a strong association between biofuel use and 

risks of anemia and stunting in children, suggesting that exposure to biofuel smoke may 

contribute to chronic nutritional deficiencies in young children. 
iv

KEY WORDS: air pollution, anemia, biomass, child, indoor, smoke, stunting 

ABBREVIATIONS: 

ARI Acute respirator infection 

BMI Body mass smoke 

CI Confidence interval 

CO Carbon monoxide 

ETS Environmental tobacco smoke 

NFHS National Family Health Survey 

PM2.5 Particulate matter less than 2.5 micrometers in diameter 

PM10 Particulate matter less than 10 micrometers in diameter 

RRR Relative risk ratio 

ACKNOWLEDGEMENTS 

The authors thank Gayle Yamashita for computer programming and Sally Dai and Shane Khan 

for research assistance. 
5

INTRODUCTION

Reliance on biomass fuels for cooking and heating exposes many women and young children in 

developing countries to high levels of air pollution indoors. Biofuel smoke exposure has been 

linked to reduced birth weight and to acute respiratory infections (ARI) and mortality in early 

childhood, but little is known about its effects on the nutritional status and physical growth of 

children. This study investigates the association between household use of unprocessed biofuels 

for cooking and heating and prevalence of anemia and stunting in children in India, using data 

from a large, nationally-representative household survey conducted in 1998–99. 

According to the survey, almost half of children under three years of age (48 percent) suffered 

from moderate-to-severe levels of anemia, and a similar proportion (46 percent) were stunted (1). 

Chronic childhood undernutrition, which can result in stunting, is a known source of ill health 

and death (2, 3). According to a recent comparative risk assessment by the World Health 

Organization, undernutrition is estimated to be, by far, the largest contributor to the global 

burden of disease (4). Widespread childhood anemia is also a major problem because it can 

result in impaired cognitive performance, behavioral and motor development, coordination, 

language development, and scholastic achievement, as well as increased susceptibility to a host 

of childhood diseases (5-7).

Biofuels are at the low end of the energy ladder in terms of combustion efficiency and 

cleanliness (8). Smoke from biomass combustion produces a large number of health-damaging 

air pollutants including respirable particulate matter, carbon monoxide (CO), nitrogen oxides, 

formaldehyde, benzene, 1,3 butadiene, polycyclic aromatic hydrocarbons (such as 

benzo[a]pyrene), and many other toxic organic compounds. In developing countries, large 

proportions of households rely on biofuels for cooking and space heating. The fuels are typically 

burned in simple, inefficient, and mostly unvented household cookstoves, which, when 

combined with poor ventilation, generate large volumes of smoke indoors (9). Moreover, these 

cookstoves are typically used for several hours each day at times when people are present, 

resulting in much higher exposure to indoor air pollutants than from outdoor sources (10). 
6

In such settings, daily average and peak exposures to air pollutants often far exceed safe levels 

recommended by the World Health Organization (11). A comparison of typical levels of CO, 

PM10, and PM2.5 in developing-country homes using biofuels with the United States 

Environmental Protection Agency’s standards for 24-hour average levels concluded that indoor 

concentrations of these pollutants in biofuel-using developing-country homes usually exceed the 

guideline levels by several-fold (9). Exposure is usually much greater among women, who tend 

to do most of the cooking (12), and among young children who tend to stay indoors and who are 

often carried on their mother’s back or lap while she cooks (13). 

Studies in India, mostly in biofuel-using rural homes, have measured kitchen area particulate 

matter concentrations of 4,000–21,000 ȝg/m3

 and 2–5-hour daily exposures of 3,600–6,800 

ȝg/m3

 during cooking (14). A recent study using time-activity data from 412 rural homes in 

south India estimated a 24-hour average exposure of 573 ȝg/m3

 in solid-fuel-using households, 

compared with 80 ȝg/m3

 in households using gas for cooking (15). Another study in western 

India measured indoor CO levels of 156 mg/m3

 for cooking with wood and 144 mg/m3 for 

cooking with dung, compared with 14 mg/m3

 for cooking with gas (16). Such high exposures 

have been linked to adverse pregnancy outcomes, ARI among children, and chronic bronchitis 

and lung cancer among women, leading to estimates of hundreds of thousands of premature 

deaths annually in India (17, 18). Although there has been speculation about a link between 

biofuel smoke and anemia and stunting, we are aware of no empirical studies on this topic.

The Indian survey measured height, weight, and blood hemoglobin levels of children below three 

years of age and their mothers. The survey also collected information on cooking and heating 

fuels, fuel mix, and tobacco smoking for all persons included in the survey. Such data are 

relatively rare in developing-country settings and provide a unique opportunity to explore the 

relationship between exposure to biofuel smoke and prevalence of anemia and stunting in 

children. 

The mechanisms by which biofuel smoke may contribute to anemia and stunting are only 

partially understood. Biofuel smoke contains large quantities of CO, which binds with 

hemoglobin (necessary for transporting oxygen to body tissues), forms carboxyhemoglobin, and 
7

reduces the quantity of hemoglobin in the blood, thereby causing anemia. Smoke exposure can 

also contribute to stunting by causing not only anemia but also reduced birth weight (19, 20), 

ARI (21, 22), and other childhood diseases.
8

MATERIAL AND METHODS 

Data

Data are from India’s second National Family Health Survey (NFHS-2), conducted in 199899.

NFHS-2 collected demographic, socioeconomic, and health information from a nationally 

representative probability sample of 92,486 households. All states of India are represented in the 

sample, covering more than 99 percent of country’s population. The sample is a multi-stage 

cluster sample with an overall response rate of 98 percent. Details of sample design, including 

sampling frame and sample implementation, are provided in the basic survey report for all India 

(1). The analysis here is based on 29,768 children under aged 0–35 months living in the sample 

households.

Response variables 

To assess the physical growth of children, measurements of weight and height/length were 

obtained for children born in the three years preceding the survey. Weight was measured using a 

solar-powered digital scale with an accuracy of ±100 g, and height was measured using an 

adjustable wooden measuring board, especially designed to provide accurate measurements (to 

the nearest 0.1 cm) in a field situation. Using these data, a child was defined as stunted if his or 

her height-for-age Z-score was more than two standard deviation (s.d.) units below the median of 

an international reference population (23, 24). We use a three-category variable for stunting in 

the analysis: not stunted (Z -2 s.d.), moderately stunted (-3 s.d.Z<-2 s.d.), severely stunted 

(Z<-3 s.d.).

To assess the anemia status of children and their mothers, blood hemoglobin levels were 

measured using the portable HemoCue system. The system uses a drop of blood from a finger 

prick (or heel prick for infants below six months), which is drawn into a cuvette and then 

inserted into a portable, battery-operated instrument to obtain a digital reading on hemoglobin 

concentration. The hemoglobin measurements were adjusted for altitude. Children were 

categorized as not anemic (11.0 g/dl), mildly anemic (10.0–10.9 g/dl), moderately anemic (7.0–

9.9 g/dl), or severely anemic (<7.0 g/dl). Because the proportion of severely anemic children is 

small (5 percent) in the sample, we use a three-category response variable for anemia—no 

anemia, mild anemia, moderate/severe anemia. 
9

Predictor variables 

Exposure to biofuel smoke is ascertained indirectly by type of fuel used for cooking or heating. 

The survey used a ten-fold classification of cooking fuel—wood, crop residues, dung cakes, 

coal/coke/lignite, charcoal, kerosene, electricity, liquid petroleum gas, biogas, and a residual 

category of other fuels. The question was, “What type of fuel does your household mainly use 

for cooking?” followed by the above list of fuels. The survey also included a second multipleresponse question, “What other types of fuel does your household commonly use for cooking or 

heating?” with the same ten-fold classification of fuels. Using this information, households were 

grouped into three categories representing extent of exposure to biofuel smoke—high exposure 

group (only biofuels: wood, crop residues, or dung cakes), low exposure group (only cleaner 

fuels: electricity, liquid petroleum gas, biogas, or kerosene), and medium exposure group (a mix 

of biofuels and cleaner fuels or coal/coke/lignite/charcoal). This three-category classification of 

fuels is the principal predictor variable. 

The survey also collected information on tobacco smoking. The survey asked the household 

respondent, “Does anyone listed smoke?” Children living in households where one or more 

persons smoked tobacco were categorized as having exposure to ETS. 

Because the effects of biofuel smoke, as well as ETS, on the prevalence of anemia and stunting 

are likely to be confounded with other factors, it is necessary to statistically control, or adjust, for 

such factors. Factors, identified in previous research as covariates of childhood nutritional status, 

include child’s age (0–5, 6–11, 12–23, 24–35 months), sex (boy, girl), birth order (1, 2, 3, 4+), 

iron supplementation during pregnancy, ARI in the preceding two weeks, diarrhea in the 

preceding two weeks, malaria in the preceding three months; mother’s age at childbirth (13–24, 

25–34, 35–49 years), body mass index (BMI) (<18.5, 18.5–25.0, 25.0 kg/m2), anemia status 

(none, mild, moderate/severe), education (illiterate, below middle complete, middle complete or 

higher); religion of household head (Hindu, Muslim, other), caste/tribe (scheduled caste or 

scheduled tribe, other backward class, other); house type (pucca, semi-pucca, kachha), separate 

kitchen availability, household crowding (<3 persons/room, 3+ persons/room), household living 

standard (low, medium, high); residence (urban, rural); and region of residence (north, central-
10

west, east-northeast, south). (See footnotes to tables 1 and 2 for more details on definitions of 

variables.) 

Analysis

We use multinomial logistic regression to estimate relative risks of suffering from anemia (none, 

mild, moderate/severe) and stunting (none, moderate, severe) among children from households 

using only biofuels and household using a mix of biofuels and cleaner fuels relative to children 

from households using only cleaner fuels, after controlling for ETS and other potentially 

confounding factors. We also included interaction terms between biofuel use and ETS to test if 

exposure to tobacco smoke modifies the effect of exposure to biofuel smoke and vice versa, but 

this effect was not significant and did not alter the independent effects of biofuel smoke and 

ETS. In the final analysis, this interaction term was not included. Since blood hemoglobin levels 

and stunting in vary young children (below six months) are not likely to be associated with 

exposure to biofuel smoke, multivariate analyses were limited to children age 6–35 months. A 

number of alternative regression models were estimated using different combinations of the 20 

potentially confounding variables mentioned above. 

In the survey, certain states and certain categories of households were over-sampled and nonresponse rates varied from one geographical area to another. In our analysis, weights are used to 

restore the representativeness of the sample (1). Results are presented in the form of relative risk 

ratios (RRR) with significance levels and 95 percent confidence intervals. The estimation of 

confidence intervals adjusts for clustering at the level of the primary sampling unit. In the case of 

mothers who had more than one child during the 3-year period, we restrict the analysis to the last 

birth in order to avoid any clustering at the mother level. Multinomial logistic regression models 

are estimated using the STATA statistical software package (25). 
11

Human subjects informed consent 

The analysis is based on secondary analysis of existing survey data with all identifying 

information removed. The survey was approved by the ethical review boards of the 

implementing agencies and the Indian government. Participation in the survey was totally 

voluntary. The survey obtained informed consent from each respondent (in this case, mothers of 

children included in the analysis) before asking questions, and separately before obtaining 

height, weight, and blood hemoglobin measurements. The hemoglobin test result was explained 

to the mother, and for anemic children, the mother was advised to seek medical treatment. For 

severely anemic children, consent for medical referral was obtained from the mother, and where 

mothers consented, a list of severely anemic children was provided to the local health provider 

for follow-up.
12

RESULTS

Characteristics of children 

About two-thirds (64 percent) of the children live in households using only biofuels for cooking 

and heating, another 24 percent live in household using a mix of biofuels and cleaner fuels or 

coal/coke/lignite/charcoal (table 1). The proportion using biofuels is much greater in rural areas 

(78 percent) than in urban areas (17 percent). On the other hand, only two percent of rural 

households exclusively use cleaner fuels, compared with 47 percent of urban households. One in 

two children live in households where at least one adult smokes tobacco regularly. This 

proportion is greater in rural area than in urban areas. Children are distributed more or less 

evenly by age. Fifty-two percent are boys and 48 percent are girls. Thirty percent of children are 

birth order four or higher. The proportion of higher-order births is much greater in rural areas 

than in urban areas, consistent with higher fertility in rural areas. Also as expected, mothers of 

rural children are considerably less likely to have received iron supplementation during 

pregnancy (52 percent) than mothers of urban children (76 percent). One in five children 

suffered from an acute respiratory infection in the two weeks preceding the survey, and a similar 

proportion suffered from diarrhea in the same period. Four percent of children suffered from an 

episode of malaria in the preceding three months. Three-fifths were born to young mothers aged 

13–24, and a similar proportion have illiterate mothers. Forty percent have undernourished 

mothers (BMI<18.5 kg/m2

), and 56 percent have anemic mothers (19 percent with moderate-tosevere anemia). Twenty-one percent belong to non-Hindu households and 31 percent belong to a 

scheduled-caste or scheduled-tribe household. Thirty-seven percent live in kachha (poor quality) 

houses, 55 percent live in houses without a separate kitchen, and another 55 percent live in 

crowded households with three or more persons per room. Forty-seven percent live in lowstandard-of-living households and only 13 percent live in high-standard-of-living households. 

About four-fifths (78 percent) live in rural areas. By geographic region, 18 percent of the 

children are from the South, and the proportions in the other regions range from 26 percent to 29 

percent.
13

Table 1 Sample distribution of children aged 0-35 months by fuel type and other selected characteristics, and by 

urban/rural residence, India 1998-99 

Characteristic Urban Rural Total 

Biofuel smoke* 

 Biomass fuels 17 78 64 

 Fuel mix 36 20 24 

 Cleaner fuel 47 2 12 

Environmental tobacco smoke (ETS)† 

 Yes 41 54 51 

 No 59 46 49 

Age of child (months) 

 0-5 15 17 16 

 6-11 17 16 16 

 12-23 34 34 34 

 24-35 34 33 34 

Sex of child 

 Boy 52 52 52 

 Girl 48 48 48 

Birth order 

 1 34 25 27 

 2 30 24 26 

 3 16 18 18 

 4 + 21 32 30 

Iron supplements during pregnancy 

 Yes 76 52 57 

 No 24 48 43 

Suffered from ARI‡ in past 2 weeks 

 Yes 16 21 20 

 No 84 79 80 

Suffered from diarrhea in past 2 weeks 

 Yes 19 19 19 

 No 81 81 81 

Suffered from malaria in past 3 months 

 Yes 2 4 4 

 No 98 96 96 

Mother's age at childbirth (years) 

 13-24 59 61 61 

 25-34 38 34 35 

 35-49 4 5 5 

Mother's body mass index (kg/m2) 

 < 18.5 32 42 40 

 18.5–25.0 57 55 56 

 25.0 11 2 4 

 Continued...
14

Table 1-Continued 

Characteristic Urban Rural Total 

Mother's anemia status§ 

 None 51 42 44 

 Mild 34 38 37 

 Moderate/severe 15 20 19 

Mother's education 

 Illiterate 36 67 60 

 Literate, <middle complete 20 17 17 

 Middle complete or higher 44 16 22 

Religion 

 Hindu 71 81 79 

 Muslim 23 14 16 

 Other# 7 5 5 

Caste/tribe** 

 Scheduled caste/scheduled tribe 21 33 31 

 Other backward class 30 33 32 

 Other 49 34 37 

House type†† 

 Pucca 61 16 26 

 Semi-pucca 28 40 37 

Kachha 11 44 37 

Separate kitchen 

 Yes 59 41 45 

 No 41 59 55 

Crowding 

 < 3 persons per room 50 43 45 

 3 persons per room 50 57 55 

Standard of living‡‡ 

 Low 18 55 47 

 Medium 51 37 40 

 High 31 8 13 

Residence 

 Urban 100 0 22 

 Rural 0 100 78 

Geographic region§§ 

 North 24 28 27 

 Central and West 37 26 29 

 East and Northeast 14 30 26 

 South 24 16 18 

 

Number of children## 6,482 22,599 29,081 

Continued...
15

Table 1-Continued *Biomass fuels: wood, animal dung, or crop residues; fuel mix: mix of biomass fuels and cleaner fuels, or 

coal/coke/lignite; cleaner fuel: kerosene, petroleum gas, biogas, or electricity. 

†Child lives in a household where one or more persons currently smoke. 

‡

 ARI is defined as coughing accompanied by short, rapid breathing. 

§ Mild anemia: blood hemoglobin level 10.0-10.9 g/dl for pregnant women and 10.0-11.9 g/dl for nonpregnant 

women; moderate anemia: blood hemoglobin level 7.0-9.9 g/dl; and severe anemia: blood hemoglobin level <7.0 

g/dl. 

#

 Sikh, Buddhist, Christian, Jain, Jewish, Zorastrian, etc. 

** Scheduled castes (SC), scheduled tribes (ST), and other backward classes are those castes and tribes designated 

by the Government of India as socially and economically backward and in need of protection from social injustice 

and exploitation. 

†† Kachha houses are made from mud, thatch or low-quality materials. Pucca houses are made from high-quality 

materials (such as bricks, tiles, cement, and concrete) throughout, including roof, walls, and floor. Semi-pucca

houses are made from partly low-quality materials and partly high-quality materials. 

‡‡ Standard of living index (SLI) is calculated by adding the scores assigned to the durable goods in the household 

as following: 4 for a car or tractor; 3 each for a moped/scooter/motorcycle, telephone, refrigerator, or color 

television; 2 each for a bicycle, electric fan, radio/transistor, sewing machine, black and white television, water 

pump, bullock cart, or thresher; and 1 each for a mattress, pressure cooker, chair, cot/bed, table, or clock/watch. 

Index scores range from 0-5 for low SLI, 6-15 for medium SLI, 16-42 for high SLI. 

§§ North: Jammu & Kashmir, Himachal Pradesh, Haryana, Punjab, Delhi, Uttar Pradesh; Central and West: 

Maharashtra, Gujarat, Madhya Pradesh, Rajasthan; East and Northeast: Bihar, West Bengal, Orissa, Assam, 

Arunachal Pradesh, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Tripura; South: Andhra Pradesh, 

Karnataka, Kerala, Tamil Nadu, Goa. 

## Number of children varies slightly for individual variables depending on the number of missing values. 

Prevalence of childhood anemia and stunting 

Overall, 71 percent of the children in our sample are anemic—23 percent are mildly anemic, and 

48 percent are moderately to severely anemic (table 2). Children living in households using only 

biofuels are much more likely to be moderately-to-severely anemic (51 percent) than those living 

in households using only cleaner fuels. The prevalence of moderate-to-severe anemia is 

noticeably higher among children of undernourished, anemic, and less-educated mothers. It is 

also higher among children in scheduled-caste and scheduled-tribe households and in poorer 

households. Prevalence of mild anemia does not vary much by fuel type or by any of the other 

characteristics.
16

Table 2 Prevalence of anemia and stunting in children aged 0-35 months by fuel type and other selected 

characteristics, India 1998-99 

 Anemia* Stunting†

Characteristic Mild 

Moderate/ 

severe Moderate Severe 

India 23 48 23 23 

Biofuel smoke 

 Biomass fuels 23 51 24 29 

 Fuel mix 23 46 22 17 

 Cleaner fuel 24 39 19 10 

Environmental tobacco smoke 

(ETS) 

 Yes 23 49 23 26 

 No 24 47 22 21 

Age of child (months) 

 0-5 24 33 12 5 

 6-11 27 44 20 11 

 12-23 22 55 28 30 

 24-35 22 49 24 32 

Sex of child 

 Boy 23 50 22 22 

 Girl 24 46 23 25 

Birth order 

 1 24 45 22 18 

 2 24 46 22 20 

 3 21 51 24 25 

 4 + 23 51 23 31 

Iron supplements during pregnancy 

 Yes 23 46 22 18 

 No 23 51 23 31 

Suffered from ARI in past 2 weeks 

 Yes 24 52 24 24 

 No 23 47 22 23 

Suffered from diarrhea in past 2 

weeks 

 Yes 24 50 24 25 

 No 23 48 22 23 

Suffered from malaria in past 3 

months 

 Yes 23 51 24 28 

 No 23 48 23 23 

 Continued...
17

Table 2-Continued 

 Anemia* Stunting†

Characteristic Mild 

Moderate/ 

severe Moderate Severe 

Mother's age at childbirth (years) 

 13-24 23 48 24 23 

 25-34 23 47 21 24 

 35-49 24 48 19 29 

Mother's body mass index (kg/m2) 

 < 18.5 23 54 25 26 

 18.5–25.0 24 45 22 22 

 25.0 24 38 15 12 

Mother's anemia status 

 None 24 42 22 21 

 Mild 24 50 23 23 

 Moderate/severe 22 59 22 28 

Mother's education 

 Illiterate 22 53 24 30 

 Literate, <middle complete 25 47 23 19 

 Middle complete or higher 25 38 19 11 

Religion 

 Hindu 23 49 23 24 

 Muslim 25 46 23 25 

 Other 21 45 20 14 

Caste/tribe 

 Scheduled caste/scheduled tribe 22 54 24 28 

 Other backward class 24 46 22 23 

 Other 24 45 22 19 

House type 

 Pucca 23 42 20 15 

 Semi-pucca 23 49 24 25 

Kachha 23 51 23 29 

Separate kitchen 

 Yes 24 45 21 19 

 No 23 51 24 28 

Crowding 

 < 3 persons per room 24 45 21 20 

 3 persons per room 23 51 24 26 

Standard of living 

 Low 23 52 24 30 

 Medium 24 46 22 21 

 High 23 40 18 11 

Residence 

 Urban 24 44 20 16 

 Rural 23 49 23 26 

 Continued...
18

Table 2-Continued 

 Anemia* Stunting† 

Characteristic Mild 

Moderate/ 

severe Moderate Severe 

Region 

 North 21 50 24 28 

 Central and West 23 51 24 23 

 East and Northeast 27 48 22 26 

 South 22 43 21 14 

 

Number of children 21,381 21,660 

*Childhood anemia is defined as a blood hemoglobin level of less than 11.0 g/dl. Mild anemia: blood 

hemoglobin level 10.0-10.9 g/dl; moderate anemia: blood hemoglobin level 7.0-9.9 g/dl; and severe anemia: 

blood hemoglobin level <7.0 g/dl. 

† Stunting is a measure of linear growth retardation in children. A child whose height-for-age is more than two 

standard deviation units below the median of the International Reference Population is defined as stunted. 

Note: For definitions of other variables, see footnotes to table 1. 

Forty-six percent of the children are stunted—23 percent moderately stunted and 23 percent 

severely stunted. Prevalence of both moderate and severe stunting is much higher among 

children living in households using biofuels than among children living in households using only 

cleaner fuels. Children in biofuel-using households are about three times as likely to be severely 

stunted as those in cleaner-fuel-using households. The proportion severely stunted is higher 

among children living in households where at least one person smokes tobacco, and it increases 

with age and birth order of child. Iron supplementation during pregnancy is strongly negatively 

associated with severe stunting. Children of less-educated, undernourished, and anemic mothers 

are more likely to be severely stunted than other children, as are children from poorer and 

scheduled-caste and scheduled-tribe households. Children living in urban areas and those in the 

South region are less likely to be severely stunted. Associations of moderate stunting with these 

characteristics tend to be similar but weaker. 

Effects of biofuel smoke on anemia 

Table 3 shows unadjusted and adjusted effects of biofuel smoke exposure on prevalence of 

anemia among children aged 6–35 months. Effects are measured by relative risk ratios (RRRs) 

calculated from the fitted multinomial logistic regressions underlying each of the five models. 

“Unadjusted” means that effects are estimated without controlling for other variables. Control 
19

variables are introduced by adding them to the set of predictor variables. In the unadjusted case 

(Model 1), biofuel smoke is the only predictor variable. 

The unadjusted relative risk of moderate-to-severe anemia (relative to no anemia) is much 

greater among children in households using only biofuels than among children in households 

using only cleaner fuels (RRR=2.18; 95 percent confidence interval: 1.90, 2.52). The unadjusted 

relative risk of moderate-to-severe anemia is also significantly greater among children in 

households using a mix of biofuels and cleaner fuels than among children in households using 

only cleaner fuels (RRR=1.53; 95 percent confidence interval: 1.31, 1.58). Progressively adding 

controls in Models 2–5 reduces the RRRs, but even when all 20 control variables are included in 

Model 5, the relative risk of moderate-to-severe anemia remains significantly higher among 

children living in households using only biofuels (RRR=1.58; 95 percent confidence interval: 

1.28, 1.94) and among children living in households using a mix of biofuels and cleaner fuels 

(RRR=1.36; 95 percent confidence interval: 1.13, 1.63) than among children living in 

households using only cleaner fuels. The adjusted effects of biofuel smoke on mild anemia are 

smaller but in the same direction. 
20

Table 3 Unadjusted and adjusted effects of biofuel smoke, ETS, and other risk factors on anemia prevalence in children aged 6-35 months in alternative models, India 1998-99  Model 1 Model 2 Model 3 Model 4 Model 5 Characteristic Mild 

Mod/

severe Mild 

Mod/

severe Mild 

Mod/

severe Mild 

Mod/

severe Mild 

Mod/

severe

Biofuel smoke  Biomass fuels 1.56*** 2.18*** 1.57*** 2.14*** 1.52*** 2.04*** 1.43*** 1.88*** 1.25 1.58***  Fuel mix 1.24* 1.53*** 1.24* 1.51*** 1.22* 1.48*** 1.19* 1.44*** 1.13 1.36***  Cleaner fuel† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Environmental tobacco smoke (ETS)  Yes 0.98 1.08 0.98 1.08 0.97 1.07 0.95 1.03  No† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Age of child (months)  6-11† 1.00 1.00 1.00 1.00 1.00 1.00  12-23 1.05 1.59*** 1.06 1.61*** 1.07 1.61***  24-35 0.80** 1.07 0.81** 1.08 0.79** 1.07 Sex of child  Boy† 1.00 1.00 1.00 1.00 1.00 1.00  Girl 1.03 0.88** 1.03 0.88** 1.04 0.86** Birth order  1† 1.00 1.00 1.00 1.00 1.00 1.00  2 1.12 1.15* 1.13 1.15* 1.13 1.15*  3 1.07 1.37*** 1.06 1.35*** 1.02 1.24**  4 + 1.20** 1.33*** 1.17* 1.28*** 1.09 1.14 Iron supplements during pregnancy  Yes 0.86* 0.81*** 0.95 0.92  No† 1.00 1.00 1.00 1.00 Suffered from ARI in past 2 weeks  Yes 1.20** 1.26*** 1.16* 1.23***  No† 1.00 1.00 1.00 1.00 Suffered from diarrhea in past 2 weeks  Yes 1.03 1.08 1.02 1.03  No† 1.00 1.00 1.00 1.00 

Continued...
21

Table 3-Continued Model 1 Model 2 Model 3 Model 4 Model 5 Characteristic Mild 

Mod/

severe Mild 

Mod/

severe Mild 

Mod/

severe Mild 

Mod/

severe Mild 

Mod/

severe

Suffered from malaria in past 3 months  Yes 1.20 1.15 1.07 0.94  No† 1.00 1.00 1.00 1.00 Mother's age at childbirth (years)  13-24† 1.00 1.00  25-34 0.93 0.91  35-49 1.07 1.01 Mother's body mass index (kg/m2)  < 18.5 1.17** 1.46***  18.5–25.5† 1.00 1.00 

 25.0 0.98 1.03 

Mother's anemia status  None† 1.00 1.00  Mild 1.30*** 1.58***  Moderate/severe 1.97*** 2.98*** Mother's education  Illiterate† 1.00 1.00  Literate, <middle complete 1.01 0.93  Middle complete or higher 0.89 0.66*** Religion  Hindu† 1.00 1.00  Muslim 1.06 0.89  Other 0.86 0.87 Caste/tribe  Scheduled caste/scheduled tribe 1.00 1.14  Other backward class 0.91 0.91  Other† 1.00 1.00 

Continued...
22

Table 3-Continued Model 1 Model 2 Model 3 Model 4 Model 5 Characteristic Mild 

Mod / 

severe Mild 

Mod/

severe Mild 

Mod/

severe Mild 

Mod/

severe Mild 

Mod/

severe

House type  Pucca 0.95 0.90  Semi-pucca 1.03 1.03 

Kachha† 1.00 1.00 

Separate kitchen  Yes 0.92 0.95  No† 1.00 1.00 Crowding  < 3 persons per room† 1.00 1.00 

 3 persons per room 1.05 1.06 

Standard of living  Low† 1.00 1.00  Medium 0.95 0.96  High 0.98 1.09 Residence  Urban 1.11 1.22*  Rural† 1.00 1.00 Region  North 1.13 1.43***  Central and West 1.38*** 1.52***  East and Northeast 1.48*** 1.19*  South† 1.00 1.00 Number of children 16,557 16,557 16,557 16,488 16,187 * p<.05, ** p<.01, *** p<.001 †Reference category Note: For variable definitions, see footnotes to tables 1 and 2. 
23

With biofuel smoke controlled, ETS does not have a significant effect on the risk of anemia in 

any of Models 2–5. The adjusted relative risk of anemia is much greater among children of 

undernourished and anemic mothers (Model 5). The adjusted relative risk of moderate-to-severe 

anemia is about three-times greater among children of mothers with moderate-to-severe anemia 

than among children of mothers with no anemia. Children of mothers with middle complete or 

higher education have a significantly lower relative risk of moderate-to-severe anemia than 

children of illiterate mothers. The relative risk of anemia is significantly higher among children 

who suffered from ARI in the preceding two weeks, but this may be due to reverse causation 

inasmuch as anemic children are more likely to have suffered from ARI. Child’s age, sex, birth 

order, urban residence, and region also have significant effects on the relative risk of moderateto-severe anemia. 

Effects of biofuel smoke on stunting 

The unadjusted relative risk of severe stunting is much higher among children in households 

using only biofuels than among children in households using only cleaner fuels (RRR=5.12; 95 

percent confidence interval: 4.30, 6.11) (table 4). The unadjusted relative risk of severe stunting 

is also significantly higher among children in households using a mix of biofuels and cleaner 

fuels than among children in households using only cleaner fuels (RRR=1.96; 95 percent 

confidence interval: 1.62, 2.38). Progressively adding controls in Models 2–5 reduces the RRRs, 

but even when all 20 control variables are included in Model 5, the relative risk of severe 

stunting is significantly higher among children living in households using only biofuels 

(RRR=1.90; 95 percent confidence interval: 1.49, 2.42) and among children living in households 

using a mix of biofuels and cleaner fuels (RRR=1.26; 95 percent confidence interval: 1.00, 1.58) 

than among children living in households using only cleaner fuels. Additionally controlling for 

child’s anemia status reduces these effects, but only slightly (Model 6). The adjusted effects of 

biofuel smoke on moderate stunting are smaller but in the same direction. 
24

Table 4 Unadjusted and adjusted effects of biofuel smoke, ETS, and other risk factors on stunting prevalence in children aged 6-35 months in alternative models, India 1998-99 

 Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Characteristic Mod Severe Mod Severe Mod Severe Mod Severe Mod Severe Mod Severe Biofuel smoke  Biomass fuels 2.16*** 5.12*** 2.15*** 4.81*** 2.08*** 4.42*** 1.93*** 3.65*** 1.25* 1.90*** 1.24 1.84***  Fuel mix 1.41*** 1.96*** 1.40*** 1.89*** 1.37*** 1.78*** 1.34*** 1.69*** 1.08 1.26* 1.07 1.21  Cleaner fuel† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Environmental tobacco smoke (ETS)  Yes 1.03 1.27*** 1.03 1.26*** 1.02 1.22*** 0.95 1.11 0.94 1.09  No† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Age of child (months)  6-11† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00  12-23 2.38*** 4.85*** 2.42*** 5.04*** 2.52*** 5.28*** 2.39*** 4.95***  24-35 1.96*** 5.15*** 2.00*** 5.37*** 2.08*** 5.76*** 2.04*** 5.67*** Sex of child  Boy† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00  Girl 1.07 1.16** 1.07 1.15** 1.07 1.13* 1.08 1.15** Birth order  1† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00  2 1.04 1.11 1.03 1.08 1.06 1.12 1.02 1.11  3 1.33*** 1.55*** 1.31*** 1.46*** 1.23** 1.32*** 1.14 1.26**  4 + 1.37*** 2.06*** 1.30*** 1.80*** 1.15 1.56*** 1.11 1.56*** Child's anemia status  No anemia† 1.00 1.00 

Mild 1.10 1.14 Moderate/severe 1.44*** 1.65*** 

Iron supplements during pregnancy  Yes 0.79*** 0.53*** 0.93 0.70*** 0.92 0.70***  No† 1.00 1.00 1.00 1.00 1.00 1.00 Suffered from ARI in past 2 weeks  Yes 1.08 1.07 1.06 1.00 1.03 0.98  No† 1.00 1.00 1.00 1.00 1.00 1.00 

Continued...
25

Table 4-Continued Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Characteristic Mod Severe Mod Severe Mod Severe Mod Severe Mod Severe Mod Severe Suffered from diarrhea in past 2 weeks  Yes 1.16* 1.27*** 1.10 1.17* 1.10 1.17*  No† 1.00 1.00 1.00 1.00 1.00 1.00 Suffered from malaria in past 3 months  Yes 1.04 1.09 0.92 0.93 0.92 0.95  No† 1.00 1.00 1.00 1.00 1.00 1.00 Mother's age at childbirth (years)  13-24† 1.00 1.00 1.00 1.00  25-34 0.86* 0.79*** 0.87* 0.78***  35-49 0.69** 0.79 0.70* 0.77* Mother's body mass index (kg/m2) < 18.5 1.10 1.08 1.10 1.07  18.5–25.5† 1.00 1.00 1.00 1.00 

 25.0 0.86 0.87 0.86 0.81 

Mother's anemia status  None† 1.00 1.00 1.00 1.00  Mild 1.11 1.15* 1.07 1.11  Moderate/  severe 1.17* 1.45*** 1.08 1.30*** Mother's education  Illiterate† 1.00 1.00 1.00 1.00  Literate, <middle  complete 0.80** 0.66*** 0.81** 0.66***  Middle complete  or higher 0.70*** 0.48*** 0.70*** 0.50*** Religion  Hindu† 1.00 1.00 1.00 1.00  Muslim 1.17 1.23* 1.13 1.22*  Other 0.76* 0.72** 0.77* 0.72** Caste/tribe  Scheduled caste/  scheduled tribe 1.23** 1.39*** 1.21** 1.38***  Other backward  class 1.11 1.36*** 1.10 1.37***  Other† 1.00 1.00 1.00 1.00 

 Continued...
26

Table 4-Continued Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Characteristic Mod Severe Mod Severe Mod Severe Mod Severe Mod Severe Mod Severe House type  Pucca 1.05 0.91 1.07 0.90  Semi-pucca 1.08 1.02 1.08 1.01 

Kachha† 1.00 1.00 1.00 1.00 

Separate kitchen  Yes 0.95 0.93 0.96 0.94  No† 1.00 1.00 1.00 1.00 Crowding  < 3 persons per  room† 1.00 1.00 1.00 1.00 

 3 persons per 

 room 1.17** 1.11 1.18** 1.10*** 

Standard of living  Low† 1.00 1.00 1.00 1.00  Medium 0.84** 0.80*** 0.87 0.80***  High 0.65*** 0.56*** 0.65*** 0.54*** Residence  Urban 0.97 1.06 0.98 1.08  Rural† 1.00 1.00 1.00 1.00 Region  North 1.73*** 2.97*** 1.70*** 2.98***  Central and West 1.44*** 2.14*** 1.40*** 2.08***  East and Northeast 1.18* 1.80*** 1.22* 1.78***  South† 1.00 1.00 1.00 1.00 Number of children 16,646 16,646 16,646 16,579 15,741 14,980 * p<.05, ** p<.01, *** p<.001 †Reference category Note: For variable definitions, see footnotes to tables 1 and 2. 
27

With the effects of biofuel smoke and other factors controlled, ETS does not have any significant 

effect on the risks of moderate or severe stunting. The adjusted relative risk of severe stunting is 

much greater among older and higher-birth-order children (Model 6). The relative risks of 

moderate and severe stunting are significantly greater among children with moderate-to-severe 

anemia than among non-anemic children. Children born to mothers who received iron 

supplementation during pregnancy have a significantly lower relative risk of severe stunting than 

children of mothers who did not receive such supplementation. The relative risk of severe 

stunting is significantly higher among children who suffered from diarrhea in the preceding two 

weeks than those who did not. Children of younger, less-educated, and anemic mothers have a 

significantly higher relative risk of severe stunting than other children. Unexpectedly, mother’s 

BMI does not have any significant adjusted effects on stunting in their children. On the other 

hand, children living in richer, less-crowded, non-Hindu/non-Muslim, upper-caste/class 

households and children in the south region have significantly lower adjusted relative risks of 

severe stunting than other children. 

The adjusted effects of biofuel use on anemia and stunting are similar in magnitude and direction 

when the above analyses were repeated for boys and girls separately and for urban and rural 

areas separately (as shown in table 5). 
28

Table 5 Adjusted effects of biofuel smoke on the prevalence of anemia and stunting in children aged 6-35 months by sex and by urban/rural residence, India 1998-99 

ANEMIA 

 Boy Girl Urban Rural Characteristic Mild 

Moderate/ 

Severe Mild 

Moderate/ 

Severe Mild 

Moderate/ 

Severe Mild 

Moderate/ 

Severe 

Biofuel smoke  Biomass fuels 1.11 1.51** 1.46* 1.65*** 1.57* 1.66** 1.15 1.65**  Fuel mix 1.01 1.36** 1.30* 1.37* 1.13 1.27 1.07 1.41*  Cleaner fuel† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Number of children 8,701 7,486 4,460 11,727 

STUNTING 

 Boy Girl Urban Rural Characteristic Moderate Severe Moderate Severe Moderate Severe Moderate Severe Biofuel smoke  Biomass fuels 1.16 1.86*** 1.35 1.84** 1.20 1.67** 1.28 2.36***  Fuel mix 1.07 1.21 1.09 1.22 1.13 1.13 1.07 1.55  Cleaner fuel† 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Number of children 8,049 6,931 4,216 10,764 * p<.05, ** p<.01, *** p<.001 †Reference category Note: Adjusted effects are based on full models in Tables 3 and 4 run separately for boys and girls and for urban and rural areas. For variable definitions, see footnotes 

to tables 1 and 2. 
29

DISCUSSION 

Household use of unprocessed biofuels for cooking and heating exposes many women and young 

children in developing countries to high levels of toxic air pollutants indoors. Anemia and 

stunting among young children are serious problems in India. About one in two children under 

three years of age suffer from moderate-to-severe anemia and a similar proportion from 

moderately-to-severe stunting.

Our analysis shows that exposure to biofuel smoke is significantly associated with prevalence of 

anemia and stunting in young children, independent of ETS, child’s age, sex, recent episodes of 

illness, maternal education and nutritional status, household living standard, and other factors. 

Children in households using a mix of biofuels and cleaner fuels also have a significantly higher 

prevalence of anemia and stunting than children in households using only cleaner fuels. These 

results suggest that household use of biofuels for cooking and heating may contribute to the risks 

of anemia and stunting in young children, independently of other factors.

With effects of biofuel smoke and other factors controlled, the effects of exposure to ETS on 

anemia and stunting are small and not statistically significant. Moreover, tests for interaction 

between the effects of biofuel smoke and ETS indicated no modifying effects. 

The analysis confirmed a strong positive relationship between mother’s anemia and child’s 

anemia. With other factors controlled, the relative risk of moderate-to-severe anemia was about 

three times greater among children of mothers with moderate-to-severe anemia than among 

children of mothers with no anemia. The study also confirmed a strong positive association 

between anemia and stunting in children. 

Several measurement constraints should be kept in mind when considering the findings of this 

study. There is a possibility of some selection in the sample due to anemia- and stunting-related 

mortality. To the extent that children living in poorer biofuel-using households are more likely to 

die from anemia and stunting, our estimated effects of biofuel smoke may be downwardly 

biased. Given high prevalence of anemia and stunting and a relatively small number of deaths in 

the sample, however, the impact of this bias on our estimated effects is likely to be small. 
30

Our estimated effects are also likely to be underestimated to the extent that the effects of biofuel 

smoke on anemia and stunting are cumulative and to the extent that some households shifted 

from biofuels to cleaner fuels in recent years. The survey did not collect any information on 

history of fuel use in the household or on past episodes of ARI and other biofuel-smoke-related 

illness that would allow us to assess the magnitude of this bias. 

Another limitation is our inability to control directly for extent of use of medical services. This 

limitation is mitigated, however, by controls for several socioeconomic characteristics that are 

correlated with access to and use of medical services. 

Anemia and stunting were measured adequately in the survey, but smoke exposure was 

ascertained indirectly from type of fuel used for cooking and heating. This imperfect 

measurement also tends to bias downward our estimates of the effects of biofuel smoke on 

anemia and stunting. However, measurements in India and other developing countries show that 

the emission of pollutants from household stoves directly varies along the “energy ladder,” with 

unprocessed solid fuels producing substantially more pollution per meal cooked than liquid or 

gaseous fuels (26). Fuel type has also been shown to be a good predictor of indoor pollution 

levels in households (27).

Despite these various limitations, the consistency of both the size and direction of our estimated 

effects suggest a possible causal relationship between biofuel smoke and both anemia and 

stunting. To validate this relationship, our research needs to be followed by carefully designed 

epidemiological studies, with direct measures of smoke exposure and a careful assessment of 

past history of fuel use and illness. Such research is important in view of the high prevalence of 

anemia and stunting and the high proportion of households in India, as well as other developing 

countries that rely on biofuels for cooking and heating. 
31

REFERENCES

1. International Institute for Population Sciences (IIPS) and ORC Macro. National Family 

Health Survey (NFHS-2), 1998–99: India. Mumbai: International Institute for Population 

Sciences, 2000. 

2. Pelletier DL. Malnutrition, morbidity and child mortality in developing countries. In United 

Nations, eds. Too Young to Die: Genes or Gender? New York: Department of Economic and 

Social Affairs, Population Division, United Nations, 1998:109–32. 

3. Rice AL, Sacco L, Hyder A, et al. Malnutrition as an underlying cause of childhood deaths 

associated with infectious diseases in developing countries. Bull World Health Organ 

2000;78:1207–21.

4. World Health Organization (WHO). World Health Report 2002: Reducing Risks, Promoting 

Healthy Life. Geneva: World Health Organization, 2002. 

5. Seshadri S. Nutritional Anaemia in South Asia. In Gillespie S, ed. Malnutrition in South 

Asia: A Regional Profile. Kathmandu: Regional Office for South Asia, UNICEF, 1997: 109–

32.

6. Stoltzfus RJ. Iron-deficiency anaemia: reexamining the nature and magnitude of the public 

health problem. Summary: implications for research and programs. J Nutr 2001;131:697S–

701S.

7. World Health Organization (WHO). Focusing on anaemia: towards an integrated approach 

for effective anaemia control. Joint statement by the World Health Organization and the 

United Nations Children’s Fund. Geneva: World Health Organization, 2004. 

8. Smith KR, Liu Y. Indoor Air Pollution in Developing Countries. In Samet JM, ed. 

Epidemiology of Lung Cancer, Lung Biology in Health and Disease Series 1994;74:151–84. 

9. Bruce N, Perez-Padilla R, Albalak R. Indoor air pollution in developing countries: a major 

environmental and public health challenge. Bull World Health Organ 2000;78:1080–92. 

10. Smith KR. Indoor air pollution in developing countries: recommendations for research. 

Indoor Air 2002;12:1–7. 

11. World Health Organization (WHO). Health and Environment for Sustainable Development: 

Five Years After the Earth Summit. Geneva: World Health Organization, 1997. 

12. Behera D, Dash S, Malik SK. Blood carboxyhaemoglobin levels following acute exposure to 

smoke of biomass fuel. India J Med Res 1988;88:522–42. 
32

13. Albalak R, Frisancho AR, Keeler GJ. Domestic biomass fuel combustion and chronic 

bronchitis in two rural Bolivian villages. Thorax 1999;54:1004–8. 

14. Smith KR, Samet JM, Romieu I, et al. Indoor air pollution in developing countries and acute 

lower respiratory infections in children. Thorax 2000;55:518–32. 

15. Balakrishnan K, Sambandam S, Ramaswamy P, et al. Exposure assessment for respirable 

particulates associated with household fuel use in rural districts of Andhra Pradesh, India. J 

Expo Anal Environ Epidemiol 2004;14:S14–S25. 

16. Patel TS, Raiyani CV. Indoor air quality: problems and perspectives. In Shukla PR, ed. 

Energy Strategies and Green House Gas Mitigation. New Delhi: Allied Publishers, 1995. 

17. Smith KR, Mehta S, Maeusezahl-Feuz M. Indoor smoke from household solid fuels. In 

Ezzati M, Lopez AD, Rodgers A, Murray CJL, eds. Comparative Quantification of Health 

Risks: Global and Regional Burden of Diseases Attributable to Selected Major Risk Factors, 

Vol. 2. Geneva: World Health Organization, 2004:1437–95. 

18. Smith KR. National burden of disease in India from indoor air pollution. PNAS 

2000;97:13286–93.

19. Mishra V, Dai X, Smith KR, et al. Maternal exposure to biomass smoke and reduced birth 

weight in Zimbabwe. Ann Epidemiol 2004;14:740–7. 

20. Boy E, Bruce N, Delgado H. Birth weight and exposure to kitchen wood smoke during 

pregnancy in rural Guatemala. Environ Health Perspect 2002;110:109–14. 

21. Mishra V. Indoor air pollution from biomass combustion and acute respiratory illness in 

preschool age children in Zimbabwe. Int J Epidemiol 2003;32:847–53. 

22. Ezzati M, Kammen D. Indoor air pollution from biomass combustion and acute respiratory 

infections in Kenya: an exposure-response study. Lancet 2001;358:619–24. Erratum in 

Lancet 2001;358:1104. 

23. Dibley MJ, Goldsby JB, Staehling NW, et al. Development of normalized curves for the 

international growth reference: historical and technical considerations. Am J Clin Nutr 

1987;46:736–48.

24. Dibley MJ, Staehling N, Neiburg P, et al. Interpretation of z-score anthropometric indicators 

derived from the international growth reference. Am J Clin Nutr 1987;46:749–62. 

25. Stata Corporation. Stata/SE 8.2 for Windows, Release 8.02. College Station, TX: Stata 

Corporation, 2003. 
33

26. Smith KR, Zhang J, Uma R, et al. Greenhouse implications of household fuels: An analysis 

for India, Annu Rev Energy Environ 2000;25:741–63. 

27. Mehta S. Characterizing Exposures to Indoor Air Pollution from Household Solid Fuel Use 

in India. Berkeley: University of California, PhD Dissertation, 2002.