Abstracting and Indexing

  • PubMed NLM
  • Google Scholar
  • Semantic Scholar
  • Scilit
  • CrossRef
  • WorldCat
  • ResearchGate
  • Academic Keys
  • DRJI
  • Microsoft Academic
  • Academia.edu
  • OpenAIRE
  • Scribd
  • Baidu Scholar

Exposure to Conditions of High Concentrations of Indoor Air Pollutants and Prevalence of ARIs in Children under 5 Years of Age, in Ouagadougou/Burkina Faso

Article Information

Kafando Benoit1*, Savadogo Paul Windinpsidi2, Millogo Tieba3, Sana Adama1, Sanon Sandrine1, Kouanda Seni4, Sondo Blaise1

 

  

1University Pr. Joseph Ki-Zerbo, Public Health Laboratory, Ouagadougou, Burkina Faso

2Institute of Environment and Agricultural Research, Sol-Eau-Plante Laboratory, Ouagadougou, Burkina Faso

3Institut Africain de Sante Publique (IASP), Ouagadougou, Burkina Faso

4Institute of Health Sciences Research Ouagadougou, Burkina Faso
 

*Corresponding Author: Kafando Benoit, University Pr. Joseph Ki-Zerbo, Public Health Laboratory, Ouagadougou, Burkina Faso

 

Received: 11 June 2019; Accepted: 21 June 2019; Published: 01 July 2019

Citation:

Kafando Benoit, Savadogo Paul Windinpsidi, Millogo Tieba, Sana Adama, Sanon Sandrine, Kouanda Seni, Sondo Blaise. Exposure to Conditions of High Concentrations of Indoor Air Pollutants and Prevalence of ARIs in Children under 5 Years of Age, in Ouagadougou/Burkina Faso. Journal of Environmental Science and Public Health 3 (2019): 298-314.

View / Download Pdf Share at Facebook

Abstract

Exposure to PM2.5 in indoor air can cause respiratory infections. In Ouagadougou, concentrations of PM2.5 produced in households using biomass were found to be very high by WHO standards (25 μg/m3 for 24 hours). The objective of this study was to highlight the effect of exposure to high concentrations of PM2.5 emitted during cooking on the prevalence of acute respiratory infections (ARI) in children under 5 years of age. This was a case-control study that took place from 16 September to 15 October 2018 in sector 15 of Ouagadougou. The sample size was 125 cases and 250 controls. Data collection was carried out using a grid, by two nurses, at the CSPS in sector 15 and in households. The cases were children diagnosed with ARI and the controls were children diagnosed with a diagnosis other than ARI. The data were entered using Epi data software and analyzed using Stata 12. The associations were expressed in Odds ratios and their confidence intervals were estimated at 95%. The results showed that the use of biomass in indoor kitchens in residential buildings was linked to the occurrence of ARI in children under the age of 5. Living in a house with several bedrooms was a protective factor. This would be explained by the better ventilation within these households.

Keywords

Indoor Air Pollution, PM2.5  Biomass, Cooking, Acute respiratory infections, Child

Indoor Air Pollution articles Indoor Air Pollution Research articles Indoor Air Pollution review articles Indoor Air Pollution PubMed articles Indoor Air Pollution PubMed Central articles Indoor Air Pollution 2023 articles Indoor Air Pollution 2024 articles Indoor Air Pollution Scopus articles Indoor Air Pollution impact factor journals Indoor Air Pollution Scopus journals Indoor Air Pollution PubMed journals Indoor Air Pollution medical journals Indoor Air Pollution free journals Indoor Air Pollution best journals Indoor Air Pollution top journals Indoor Air Pollution free medical journals Indoor Air Pollution famous journals Indoor Air Pollution Google Scholar indexed journals PM2.5  Biomass articles PM2.5  Biomass Research articles PM2.5  Biomass review articles PM2.5  Biomass PubMed articles PM2.5  Biomass PubMed Central articles PM2.5  Biomass 2023 articles PM2.5  Biomass 2024 articles PM2.5  Biomass Scopus articles PM2.5  Biomass impact factor journals PM2.5  Biomass Scopus journals PM2.5  Biomass PubMed journals PM2.5  Biomass medical journals PM2.5  Biomass free journals PM2.5  Biomass best journals PM2.5  Biomass top journals PM2.5  Biomass free medical journals PM2.5  Biomass famous journals PM2.5  Biomass Google Scholar indexed journals Cooking articles Cooking Research articles Cooking review articles Cooking PubMed articles Cooking PubMed Central articles Cooking 2023 articles Cooking 2024 articles Cooking Scopus articles Cooking impact factor journals Cooking Scopus journals Cooking PubMed journals Cooking medical journals Cooking free journals Cooking best journals Cooking top journals Cooking free medical journals Cooking famous journals Cooking Google Scholar indexed journals Acute respiratory infections articles Acute respiratory infections Research articles Acute respiratory infections review articles Acute respiratory infections PubMed articles Acute respiratory infections PubMed Central articles Acute respiratory infections 2023 articles Acute respiratory infections 2024 articles Acute respiratory infections Scopus articles Acute respiratory infections impact factor journals Acute respiratory infections Scopus journals Acute respiratory infections PubMed journals Acute respiratory infections medical journals Acute respiratory infections free journals Acute respiratory infections best journals Acute respiratory infections top journals Acute respiratory infections free medical journals Acute respiratory infections famous journals Acute respiratory infections Google Scholar indexed journals Child articles Child Research articles Child review articles Child PubMed articles Child PubMed Central articles Child 2023 articles Child 2024 articles Child Scopus articles Child impact factor journals Child Scopus journals Child PubMed journals Child medical journals Child free journals Child best journals Child top journals Child free medical journals Child famous journals Child Google Scholar indexed journals wood articles wood Research articles wood review articles wood PubMed articles wood PubMed Central articles wood 2023 articles wood 2024 articles wood Scopus articles wood impact factor journals wood Scopus journals wood PubMed journals wood medical journals wood free journals wood best journals wood top journals wood free medical journals wood famous journals wood Google Scholar indexed journals chronic bronchitis articles chronic bronchitis Research articles chronic bronchitis review articles chronic bronchitis PubMed articles chronic bronchitis PubMed Central articles chronic bronchitis 2023 articles chronic bronchitis 2024 articles chronic bronchitis Scopus articles chronic bronchitis impact factor journals chronic bronchitis Scopus journals chronic bronchitis PubMed journals chronic bronchitis medical journals chronic bronchitis free journals chronic bronchitis best journals chronic bronchitis top journals chronic bronchitis free medical journals chronic bronchitis famous journals chronic bronchitis Google Scholar indexed journals carbon monoxide articles carbon monoxide Research articles carbon monoxide review articles carbon monoxide PubMed articles carbon monoxide PubMed Central articles carbon monoxide 2023 articles carbon monoxide 2024 articles carbon monoxide Scopus articles carbon monoxide impact factor journals carbon monoxide Scopus journals carbon monoxide PubMed journals carbon monoxide medical journals carbon monoxide free journals carbon monoxide best journals carbon monoxide top journals carbon monoxide free medical journals carbon monoxide famous journals carbon monoxide Google Scholar indexed journals charcoal articles charcoal Research articles charcoal review articles charcoal PubMed articles charcoal PubMed Central articles charcoal 2023 articles charcoal 2024 articles charcoal Scopus articles charcoal impact factor journals charcoal Scopus journals charcoal PubMed journals charcoal medical journals charcoal free journals charcoal best journals charcoal top journals charcoal free medical journals charcoal famous journals charcoal Google Scholar indexed journals

Article Details

1. Introduction

The combustion of biomass produces pollutants that are potentially harmful to human health. PM2.5 and carbon monoxide (CO) are the pollutants generally reported in the literature [1]. The main sources of indoor air pollution are the use of wood for meal preparation [2-4]. In the city of Ouagadougou, 60% of the households use biomass (coal and/or wood) as fuel in the cooking of their meals. This biomass is used with improved and/or traditional stoves. Compared to the WHO 24-hour limit of 25 μg/m3, concentrations of PM2.5 produced in households were found to be very high under some conditions of meal preparation such as [5-6]: i) In outdoor kitchens (110.69 μg/m3), ii) In households using the Traditional stoves and wood (95.69 μg/m3), iii) In households using wood (62.54 μg/m3), iv) In households using improved stoves and coal (27.62 μg/m3). Health problems due to exposure to high concentrations of PM2.5 are mainly related to the respiratory system. The most common pathologies are: asthma, acute respiratory infections, chronic respiratory infections (chronic bronchitis, chronic obstructive bronchopathy) [7-8]. Despite the high exposure of children in some households to high concentrations of PM2.5, few studies have examined the adverse effects of this exposure on their health. The objective of this study aimed at determining the effect of exposure to high concentrations of PM2.5 emitted during meal preparation on the prevalence of acute respiratory infections in children under the age of 5.
 

2. Study Materials and Methods

2.1 Type of study

This is a case-control study carried out from 16 September to 15 October 2018 in district 15 of the city of Ouagadougou.
 

2.2 Field and study population

District 15 of the city of Ouagadougou, one of the two districts covered by the Ecosanté project's intervention zone. Two-thirds of the dominant habitats were common low-rise courtyards and houses built with temporary materials (78%). Meals were cooked once a day in 69% of households, using traditional or improved stoves in 45% of households, and consuming wood or charcoal in 60% of households. The places where meals were cooked were mainly inside the family home (40.46%) and outside the family home, in a separate building (19%) or outdoors in the yard (38.82%). In most households (90%), children who are not yet in school are looked after by women who are in charge of cooking meals [9]. The Health center of district 15 is part of the Sig-Noghin health district, for which the CMA is the reference center. Its health area was located in the 3rd and 9th districts of the city Ouagadougou. Indeed, it includes district 15 (administrative subdivision 3) and 38 (administrative subdivision 9) of the new division. It is limited to the East by the health area’s health center (CSPS) in district 22, to the north of the health area’s health center (CSPS) of Bissighin Pazani and Marcoussi and to the South by that of district 20. According to the 2017 action plan, the population of the health area’s health center (CSPS) in district 15 was estimated at 71,683 people, including 10,541 children under the age of 5. It includes a dispensary, a maternity ward, a MEG storage facility and a cash register. On a daily basis, curative care is provided by nurses in two rooms. An average of 5000 curative care consultations is carried out per month.
 

2.3 Sample

Two groups of children were formed from children under 05 years of age received in a curative visit at the health center (CSPS) in district 15. The first group included children who were diagnosed with ARI by health workers. The second group included children with a non-ARI diagnosis. The sample size was calculated using StatCalc from Epi info 7.2.2.2.6. Considering the following parameters: power=80%, number of controls for a case: 2, percentage of exposed controls: 40%, OR=2. The sample size is 323 children, including 108 cases and 215 controls. Considering 15% refusal, the sample size becomes 375 or 125 cases and 250 controls. All children who were admitted and satisfied with the inclusion criteria, in whom the parents agreed to participate in the study, were concerned. Children were included as they were included until the required sample sizes were obtained.
 

2.4 Case definition

The case of ARI is any child under the age of 05 years who received a curative consultation at the health center (CSPS) in district 21 during the survey period and for whom the diagnosis was a respiratory infection. The definition of respiratory infection was in accordance with the WHO definition: Acute respiratory infections (ARIs) are diseases affecting the upper or lower respiratory tract, usually of infectious origin and can take very different forms, ranging from asymptomatic or benign to severe or fatal, depending on the pathogen and factors related to the environment or to the host. The respiratory tract, including the nose, throat, larynx, trachea, bronchial tubes, bronchioles or lungs. The diseases ranging from common colds to ear infections, sore throats, bronchitis, bronchiolitis and common pneumonia, sore throats, bronchitis, bronchiolitis and pneumonia [10].
 

2.5 Definition of controls

The witness in our study is any child under the age of 05 years who received a curative consultation at the health center (CSPS) in district 15 during the survey period for who was not diagnosed with an acute respiratory infection.
 

2.6 Inclusion criteria

The inclusion criteria were:

  • For cases: Two main criteria were considered: 1) live in the study area and 2) have no other pathologies outside the ARI in order to minimize diagnostic bias
  • For controls: Live in the study area, do not show symptoms of ARI for 14 days before data collection.
     

2.7 Data collection techniques

Data on children’s respiratory health were collected by a pair of two investigators holding the State Nurse diploma, trained in integrated management of childhood diseases. A grid was used to collect the child’s demographic and health data. Health data collection was done at the health center (CSPS) level every morning from 8:00 am to 12:00 pm during the survey period. At the health center (CSPS) level, the interviewers worked closely with the health workers on the curative consultation team. For each child in the sample, interviewers visited households in the afternoons and collected information about the households, the conditions for cooking and the family environment in which the children live. To this end, a data collection grid has also been developed. The information thus dealt with: types of kitchens, types of households, types of fuel, the time the meal is cooked daily in the household, the type of housing, the number of people living in the household, the number of bedrooms, the number of children under five years old and the identity of the person looking after the child.
 

2.8 Data analysis

The data were entered using Epi data software and analyzed using Stata 12. A comparison of the two groups of children was first done to ensure that they are homogeneous on Age and Sex. A description of all the variables was then done after. Proportions were used to describe qualitative variables and quantitative variables were described using averages, with astandard deviation or medians, and interquartile spaces. The frequencies of exposure to risk factors were calculated for each group. In the bivariate analysis, the estimation of the Odds Ratio to measure the association between the IRA and each risk factor studied was performed. In multivariate analysis, a logistic regression model was used in a step-by-step, bottom-up procedure. The likelihood ratio test was used to compare successive models and the adjustment of the final model was verified before reporting the results. The associations between the dependent variable and the independent variables were expressed in Odds ratio (OR) and their corresponding confidence intervals (95% CI) were estimated.
 

2.9 Description of the study variables

In addition to the independent variables already discussed in our previous article [9], the following independent variables have been added:

  • Gender: Male, female
  • Vaccination status: from the child's vaccination record, investigators checked whether the child was up to date with his/her vaccinations, in line with the current vaccination schedule
  • Breastfeeding: The investigators asked the parents the question to find out if the child is still breastfeeding or not.
  • Nutritional status: using the criterion of the brachial perimeter, the investigators were responsible for measuring it in each child and classifying it as malnourished or not malnourished
  • Humidification of nostrils with Shea butter: The investigators asked the parents the question to find out if they are used to humidifying the child's nostrils with shea butter.
  • Protection against cold and wind: The investigators observed the clothing of each child. Children who wore at least two layers of clothing were classified as "well protected from the cold and wind". The others were classified as "insufficient protection against cold and wind".
     

3. Results

A comparison of the two groups according to the age and sex of the children is presented in Table 1.
 

Case (n=125)

Control (n=250)

Chi2

P Value

Age

Less than one year

38

(30.40%)

65

(26.32%)

0.8343

0.841

Between 1 and 2 years old

38

(30.40%)

79

(31.98%)

Between 2 and 3 years old

16

(12.80%)

35

(14.17%)

More than three years

33

(26.40%)

71

(28.74%)

Gender

Male

70

(56.00%)

140

(56.00%)

 0.0018

 0.967

Female

55

(44.00%)

110

(44.00%)

Table 1: A comparison of the two groups according to the age and sex.
 

3.1 Descriptive analysis of variables

3.1.1 Socio-demographic characteristics of children: The average age of the cases and controls was 21.49 and 23.07 months respectively. The distribution of children by sex was the same for cases and controls, with 56% of boys and 44% of girls respectively.
 

3.1.2 Characteristics of children by immunization and nutritional status: Of the total sample, 363 (96.80%) were up to date with their vaccination, 118 (94.40%) in cases and 245 (98.00%) in controls. Measurements of the brachial perimeter made it possible to classify a total of 11 malnourished children, i.e. 4 cases (3.20%) and 7 controls (1.62%).


3.1.3 Practices for protecting children from the cold, wind: The practices of humidification of the nostrils with shea butter are found in 100 cases (80%) and 218 controls (87.20%). As for the wearing of at least two layers of clothing, it was found in 42 cases (33.60%) and in 77 controls (30.80%).
 

3.1.4 Meal cooking practices: Meals were prepared at least three times a day in 21 households: 10 (8%) in cases and 11 (4.45%) in controls. Indoor kitchens were found in 35 (28%) households in the cases and 58 (23.20%) households in the controls. The traditional stove was used in 16 (12.8%) households for cases and 46 (18.40%) for controls. Biomass was used in 52 (41.6%) households for cases and 96 (38.87%) households for controls.
 

3.1.5 Sociodemographic characteristics of households: In the cases, 18 (14.4%) had more than three bedrooms compared to 47 (18.80%) in the controls. In the cases 13 (10.40%) households had more than 10 inhabitants, compared to 19 (6.88%) households in the controls. The frequencies of exposure of each group to the risk factors studied are presented in Table 2.
 

Groups

Case (n=125)

Control (n=250)

Humidification of the nostrils with Shea butter

Yes

100

(80.00%)

218

(87.20%)

No

25

(20.00%)

32

(12.80%)

Protection against cold and wind

Wearing a single layer of clothing

83

(66.40%)

173

(69.20%)

Wearing at least two layers of clothing

42

(33.60%)

77

(30.80%)

Vaccination status

Up to date

118

(94.40%)

245

(98.00%)

Not up to date

7

(5.60%)

5

(2.00%)

Breastfeeding

Yes

72

(57.60%)

132

(52.80%)

No

9

(7.20%)

21

(8.40%)

Not applicable

44

(35.20%)

97

(38.80%)

Nutritional status

Malnourished

4

(3.20%)

7

(2.80%)

Not malnourished

121

(96.80%)

243

(97.20%)

Number of bedrooms

One bedroom

78

(62.40%)

146

(58.40%)

Two bedrooms

26

(20.80%)

53

(21.20%)

Three or more bedrooms

18

(14.40%)

47

(18.80%)

No answer

3

(2.40%)

4

(1.60%)

Household size

Between 1 and 5 people

70

(56.00%)

158

(63.20%)

Between 6 and 10 people

42

(33.60%)

73

(29.20%)

More than 10 people

13

(10.40%)

19

(7.60%)

Number of children under 05 years old

A child

88

(70.40%)

147

(58.80%)

Two children

23

(18.40%)

70

(28.00%)

Three or more children

14

(11.20%)

33

(13.20%)

Number of people in the same room as the child

A person

94

(75.20%)

173

(69.20%)

More than 2 people

31

(24.80%)

74

(29.60%)

No answer

0

(0.00%)

3

(1.20%)

Person in charge of the child’s care

Cooks the meal

119

(95.20%)

238

(95.20%)

Does not cook the meal

6

(4.80%)

10

(4.00%)

No answer

0

(0.00%)

2

(0.80%)

Children’s playgrounds

Court

65

(52.00%)

144

(57.60%)

Interior

15

(12.00%)

19

(7.60%)

Outside

45

(36.00%)

86

(34.40%)

No answer

0

(0.00%)

1

(0.40%)

Frequency of meal preparation

Once in a while

76

(60.80%)

182

(72.80%)

Twice

39

(31.20%)

56

(22.40%)

Three times and more

10

(8.00%)

11

(4.40%)

No answer

0

(0.00%)

1

(0.40%)

Mother’s education level

Illiterate

42

(33.60%)

82

(32.80%)

Literate / Primary

39

(31.20%)

94

(37.60%)

Secondary/higher

44

(35.20%)

74

(29.60%)

The existence of a person who smokes within the household

Yes

34

(27.20%)

46

(18.40%)

No

91

(72.80%)

204

(81.60%)

Type of kitchen

Open-air cooking

33

(26.40%)

82

(32.80%)

Indoor kitchen

35

(28.00%)

58

(23.20%)

Outdoor kitchen

57

(45.60%)

110

(44.00%)

Type of stove

Gas

73

(58.40%)

152

(60.80%)

Improved

36

(28.80%)

52

(20.80%)

Traditional

16

(12.80%)

46

(18.40%)

Type of fuel used

Gas

73

(58.40%)

154

(61.60%)

Wood

30

(24.00%)

68

(27.20%)

Coal

22

(17.60%)

28

(11.20%)

Combinations stove /fuel

Gas

73

(58.40%)

152

(60.80%)

Improved stove +Wood

14

(11.20%)

22

(8.80%)

Improved stove + coal

22

(17.60%)

30

(12.00%)

Traditional stove + wood

16

(12.80%)

46

(18.40%)

Conditions for cooking meals

Open-air kitchen + Gas

12

(9.60%)

32

(12.80%)

Outdoor kitchen + improved stoves + wood

8

(6.40%)

12

(4.80%)

Open-air kitchen + improved stoves + coal

7

(5.60%)

13

(5.20%)

Open-air kitchen + Traditional stove + Wood

6

(4.80%)

28

(11.20%)

Outdoor kitchen + Gas

13

(10.40%)

20

(8.00%)

Outdoor kitchen + improved stove + wood

5

(4.00%)

8

(3.20%)

Outdoor kitchen + Traditional stove + Wood

8

(6.40%)

17

(6.80%)

Outdoor kitchen + improved stove + coal

9

(7.20%)

13

(5.20%)

Indoor kitchen + Gas

48

(38.40%)

100

(40.00%)

Indoor kitchen + Traditional/improved stove + Wood/coal

9

(7.20%)

7

(2.80%)

Table 2: frequencies of exposure of each group to risk factors.
 

3.2 Bivariate analysis

Table 3 shows the results of the bivariate analysis.
 

Group

Unadjusted OR

Chi2

P value

[95 % CI]

Age

Less than one year

1

-

-

-

-

Between 1 and 2 years old

0.823

0.47

0.493

0.471

-1.438

Between 2 and 3 years old

0.782

0.45

0.501

0.382

-1.603

More than 3 years

0.795

0.61

0.435

0.446

-1.416

Gender

Male

1

-

-

-

-

Female

1.009

0

0.967

0.653

-1.561

Humidification of the nostrils with Shea butter

Yes

1

-

-

-

-

No

1.703

3.34

0.068

0.956

-3.035

Protection against cold and wind

Wearing a single layer of clothing

1

-

-

-

-

Wearing at least two layers of clothing

0.88

0.3

0.583

0.556

-1.392

Breastfeeding

Yes

1

-

-

-

-

No

0.786

0.32

0.57

0.341

-1.81

Non-application

0.832

0.62

0.43

0.526

1.316

Vaccination status

Up to date

1

-

-

-

-

Not up to date

2.907

3.48

0.062

0.897

-9.417

Nutritional status

Malnourished

1

-

-

-

-

Not malnourished

0.871

0.05

0.829

0.25

-3.04

Number of bedrooms

One bedroom

1

-

-

-

-

Two bedrooms

0.717

1.15

0.284

0.389

-1.321

Three or more bedrooms

0.918

0.09

0.759

0.533

-1.583

Household size

Between 1 and 5 people

1

-

-

-

-

Between 6 and 10 people

1.299

1.17

0.279

0.808

-2.086

More than 10 people

1.63

1.58

0.209

0.754

-3.523

Number of children under 05 years old

A child

1

-

-

-

-

Two children

0.549

4.8

0.029

0.318

-0.946

Three or more children

0.709

0.99

0.319

0.359

-1.4

Number of people in the same room as the child

A person

1

-

-

-

-

More than 2 people

0.771

1.09

0.297

0.472

-1.259

Children's playgrounds

Court

1

-

-

-

-

Interior

1.749

2.23

0.135

0.832

-3.675

Outside

1.159

0.39

0.534

0.728

-1.846

Frequency of cooking meal

Once a day

1

-

-

-

-

Twice a day

2.177

2.99

0.084

0.882

-5.375

Three times and more

1.668

4.24

0.047

1.019

-2.729

Mother's education level

Illiterate

1

-

-

-

-

Literate / Primary

0.810

0.61

0.434

0.477

-1.374

Secondary/higher

1.161

0.31

0.58

0.685

-1.969

Existence of a person who smokes within the household

Yes

1

-

-

-

-

No

0.604

3.84

0.051

0.362

-1.006

Type of kitchen

Open-air cooking

1

-

-

-

-

Indoor kitchen

1.554

2.22

0.137

0.865

-2.791

Outdoor kitchen

1.372

1.45

0.228

0.818

-2.301

Type of stoves

Gas

1

-

-

-

-

Improved

1.499

1.86

0.173

0.834

-2.696

Traditional

1.288

0.92

0.337

0.768

-2.16

Type of fuel

Gas

1

-

-

-

-

Wood

0.931

0.08

0.784

0.557

-1.554

Coal

1.658

2.54

0.111

0.885

-3.106

Combinations Stoves /fuel

Gas

1

-

-

-

-

Improved stoves +Wood

1.325

0.58

0.447

0.64

-2.744

Improved stoves + Coal

1.636

2.41

0.121

0.873

-3.066

Traditional stoves + wood

0.724

1

0.318

0.383

-1.368

Kitchen/stoves /fuel combinations

Indoor kitchen + Gas

1

-

-

-

-

Outdoor cooking + Gas

0.781

0.42

0.518

0.369

-1.654

Outdoor kitchen + improved stoves + wood

1.389

0.45

0.502

0.53

-3.637

Open-air kitchen + improved stoves + coal

1.122

0.05

0.819

0.419

-3.002

Open-air kitchen + Traditional stoves + Wood

0.446

2.88

0.090

0.171

-1.162

Outdoor kitchen + Gas

1.354

0.58

0.446

0.62

-2.96

Outdoor kitchen + improved stoves + wood

1.302

0.2

0.658

0.403

-4.21

Outdoor kitchen + Traditional stoves + Wood

0.98

0

0.966

0.394

-2.437

Outdoor kitchen + improved stoves + coal

1.442

0.61

0.433

0.574

-3.624

Indoor kitchen + Traditional/improved stoves + Wood/Coal

2.679

3.59

0.058

0.927

-7.738

The person who looks after the child under 05 years of age

Is the one who cooks

1

-

-

-

-

Is not the one who makes the meal

1.2

0.12

0.730

0.425

-3.386

Table 3: Results of the bivariate analysis.
 

The results of the multivariate analysis according to the selected model are shown in Table 4.
 

Group

OR Unadjusted

OR Adjusted

P value

[95% CI]

Gender

Male

1.000

-

-

-

-

Female

1.009

1.002

0.993

0.625

-1.608

Humidification of the nostrils with Shea butter

Yes

1.000

-

-

-

-

No

1.703

1.807

0.067

0.959

-3.405

Vaccination status

Up to date

1.000

-

-

-

-

Not up to date

2.907

2.394

0.176

0.676

-8.475

Nutritional status

Malnourished

1.000

-

-

-

-

Not malnourished

0.871

0.743

0.678

0.183

-3.020

Number of bedrooms 

One bedroom

1.000

-

-

-

-

Two bedrooms

0.717

0.691

0.229

0.378

-1.263

Three or more bedrooms

0.918

0.383

0.013

0.179

-0.819

Household size

Between 1 and 5 people

1.000

-

-

-

-

Between 6 and 10 people

1.299

1.496

0.150

0.864

-2.590

More than 10 people

1.630

1.915

0.188

0.728

-5.033

Frequency of meal preparation

Once in a while

1.000

-

-

-

-

Twice

2.177

1.564

0.119

0.891

-2.745

Three times and more

1.668

2.395

0.098

0.851

-6.738

Mother’s education level            

Illiterate

1.000

-

-

-

-

Literate / Primary

0.810

0.759

0.342

0.430

-1.341

Secondary/higher

1.161

0.987

0.965

0.538

-1.809

Existence of a person who smokes within the household

Yes

1.000

-

-

-

-

No

0.604

0.689

0.190

0.395

-1.202

Kitchen/stoves/fuel combinations

Outdoor cooking + Gas

1.000

-

-

-

-

Outdoor kitchen + improved stoves + wood

0.781

1.694

0.394

0.504

-5.693

Open-air kitchen + improved stoves + coal

1.389

1.709

0.383

0.513

-5.698

Open-air kitchen + Traditional stoves + Wood

1.122

0.663

0.502

0.200

-2.199

Outdoor kitchen + Gas

1.354

2.482

0.208

0.602

-10.232

Outdoor kitchen + improved stoves + wood

0.446

2.497

0.083

0.887

-7.035

Outdoor kitchen + Traditional stoves + Wood

1.302

1.386

0.586

0.429

-4.477

Outdoor kitchen + improved stoves + coal

0.980

2.131

0.209

0.654

-6.939

Indoor kitchen + Gas

1.442

1.617

0.252

0.711

-3.681

Indoor kitchen + Traditional/improved stoves + Wood/coal

2.679

3.792

0.044

1.034

-13.904

Table 4: Results of the multivariate analysis.
 

4. Discussion

Socio-demographic characteristics of children and ARIs among children under 05 years of age: The data analysis did not find an association between ARI and the socio-demographic characteristics of children. However, other authors had found that the occurrence of acute respiratory infections in children under 5 years of age was associated with the age of the children, particularly those under one year of age were the most at risk [11-13]. The same is also valid for the child's sex, which has been found by many authors, as one of the determinants of respiratory infections. The male sex being most at risk of developing respiratory infections [14-16].
 

4.1 Characteristics of children by immunization and nutritional status

The routine immunization program in Burkina Faso includes five different vaccines for the prevention of nine pathogens: (1) BCG against tuberculosis, (2) oral polio vaccine (OPV), (3) pentavalent vaccine against diphtheria, tetanus, pertussis, hepatitis B and Haemophilus influenzae type b (Penta), (4) yellow fever vaccine, and (5) anti-MV vaccine [17]. The analysis of the results of our study did not show any association between the child’s immunization status and the prevalence of ARI. However, other authors have found that partial immunization is a risk factor for the development of ARI in children under the age of 5 [18-20].
 

4.2 Child nutritional status and occurrence of ARIs

An association between the prevalence of ARIs among children under 05 years of age has not been found by our study. This result does not correspond to those of other authors who had found that nutritional deficiency was associated with decreased lung function in children [21-22]. Thus, micronutrient deficiency is a risk factor for acute respiratory infections [23-25].
 

4.3 Practices for protecting children from the cold, wind

The shea butter is rich in vitamins A, E and omega 9. Among its properties, it is effective against skin dryness and protects the skin against sunburn [26]. It is commonly used to prevent respiratory infections, by wetting the nostrils to retain dust and prevent the deposition of germs in the nasal tract. Data analysis did not find an association between this practice and the prevalence of ARI in children under 05 years of age. A statistically significant association has not also been found between the protection of children through the use of several layers of clothing and the prevalence of ARI.
 

4.4 Meal cooking practices

In the bivariate analysis, a statistically significant association was found between meal cooking frequency and prevalence of ARIs (OR: 1.640, p=0.047). This association was not found in the multivariate analysis. However, others found that the increase in exposure time to high PM2.5 concentrations was associated with ARI. Indeed, a study in Bangladesh indicated that every hour that PM2.5 concentrations exceeded 100 μg/m3 was associated with a 7% increase in the incidence of ARI in children aged 0 to 11 months [27]. Reducing exposure to PM2.5 then involves reducing the frequency of cooking meal. In the multivariate analysis, another association with ARI in children under 5 years of age was found. This was the use of biomass for cooking meals in indoor kitchens (OR=3.792, p=0.044). Similar results were found in a multi-country study conducted in 2015 [28]. In internal kitchens, the lack of a smoke evacuation system for the combustion of biomass would lead to the circulation of polluted air in all rooms. Insufficient ventilation of the bedrooms would favour a high concentration of particles in them. Thus, all room occupants would be exposed to the adverse effects of particulate matter on their respiratory health [29-33].
 

4.5 Sociodemographic characteristics of households

Children living in residential homes with more than 03 bedrooms were less likely to develop an ARI compared to those living in residential homes with only one bedroom (OR: 0.383, p=0.013). Several authors have also demonstrated this link between housing type and ARIs. Indeed, children living in high quality housing are less likely to develop ARIs related to indoor air pollution [33-36]. This would be explained by better ventilation, but also by a trend towards the use of less polluting fuels in these households, which are considered to have access to financial resources for less polluting fuels. The presence of a smoker in the household has not been identified as a risk factor for the development of ARIs in children under 5 years of age. However, several authors had demonstrated this association [37-38]. Household size, number of children under 5 years of age, child’s playgrounds and maternal education level were not also found to be significantly associated with the prevalence of ARIs. However, several studies have shown that these socio-economic factors are related to the prevalence of ARI in children under the age of 05 [23, 29, 33, 39, 40, 41].
 

5. Conclusion

The objective of the study was to demonstrate the association between exposure to conditions of high indoor air PM2.5 concentrations due to biomass combustion and the prevalence of ARI in children under the age of 5 in households in district 15 of the city of Ouagadougou. The results showed that the use of biomass for cooking meals in indoor kitchens in residential buildings was a factor that favoured the occurrence of ARIs in children under the age of 5. In addition, living in a house with several bedrooms was a protective factor against ARIs. This is linked in particular to better ventilation, but also to a trend to the use of less polluting fuels in these households considered as those with financial access to less polluting fuels.
 

Acknowledgements

We would like to thank all those who contributed to the realization of this study, in particular:

  • The “Chairepol" project (IDRC project 107347) funded by IDRC for its support;
  • The Centre's regional health department, the Commune of Ouagadougou and the Sig-noghin Health District, which authorized the data collection,
  • The Sector 15 CSPS health team for their support in data collection
  • The two nurses who carried out the data collection
  • The heads of households who have agreed to receive our interviewers.
     

References

  1. Naeher LP, Brauer M, Lipsett M, et al. Woodsmoke health effects: a review. Inhalation toxicology 19 (2007): 67-106.
  2. Bautista LE, Correa A, Baumgartner J, et al. Indoor charcoal smoke and acute respiratory infections in young children in the Dominican Republic. American journal of epidemiology 169 (2009): 572-580.
  3. Ezzati M, Lopez AD, Rodgers AA, et al. Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors. WHO (2004).
  4. Khalequzzaman M, Kamijima M, Sakai K, et al. Indoor air pollution and the health of children in biomass-and fossil-fuel users of Bangladesh: situation in two different seasons. Environmental health and preventive medicine 15 (2010): 236.
  5. Thorsson S, Holmer B, Andjelic A, et al. Carbon monoxide concentrations in outdoor wood-fired kitchens in Ouagadougou, Burkina Faso-implications for women’s and children’s health. Environmental Monitoring and Assessment 186 (2014): 4479-4492.
  6. Kafando B, Savadogo PW, Sana A, et al. Pollution de l’air intérieur par les PM5 issues des combustibles utilisés pour la cuisson des repas et risques sanitaires chez les personnes exposées: cas du secteur 15 de Ouagadougou. Environnement, Risques and Sante 3 (2019).
  7. Smith KR, Mehta S, Maeusezahl-Feuz M. Indoor air pollution from household use of solid fuels. Comparative quantification of health risks. chez global and regional burden of disease attributable to selected major risk factors 2 (2004): 1435-1493.
  8. Household air pollution and health (2018).
  9. Kafando B, Savadogo P, Millogo T, et al. Indoor air pollution and prevalence of acute respiratory infections among children in Ouagadougou. Public health 30 (2018): 575-586.
  10. UICTMR, Prise en charge de l’enfant qui tousse ou qui a des difficultés respiratoires. Guide pour les pays à faibles revenus, Paris (2005): 80.
  11. Naorat S, Chittaganpitch M, Thamthitiwat S, et al. Hospitalizations for acute lower respiratory tract infection due to respiratory syncytial virus in Thailand, 2008-2011. The Journal of infectious diseases 208 (2013): 238-245.
  12. Rowlinson E, Dueger E, Mansour A, et al. Incidence and etiology of hospitalized acute respiratory infections in the Egyptian Delta. Influenza and other respiratory viruses 11 (2017): 23-32.
  13. Gurley ES, Homaira N, Salje H, et al. Indoor exposure to particulate matter and the incidence of acute lower respiratory infections among children: a birth cohort study in urban Bangladesh. Indoor Air 23 (2013): 379-386.
  14. Ait-Khaled N, Enarson D, Bousquet J. Chronic respiratory diseases in developing countries: the burden and strategies for prevention and management. Bulletin of the World Health Organization 79 (2001): 971-979.
  15. Ponvert C. What’s new in pediatric allergology in 2009? Part 2: Ocular and respiratory allergy (a review of the international literature from late 2008 to late 2009). Revue Française d'Allergologie 50 (2010): 637-652.
  16. Lowther S, Shinoda N, Juni B, et al. Haemophilus influenzae type b infection, vaccination, and H. influenzae carriage in children in Minnesota. Epidemiology and Infection 140 (2012): 566-574.
  17. Kagone M, Ye M, Nebie E, et al. Vaccination coverage and factors associated with adherence to the vaccination schedule in young children of a rural area in Burkina Faso. Global health action 10 (2017): 1399749.
  18. Gothankar J, Doke P, Dhumale G, et al. Reported incidence and risk factors of childhood pneumonia in India: A community-based cross-sectional study. BMC public health 18 (2018): 1111.
  19. Ouedraogo SM, Toloba Y, Ouedraogo G, et al. Epidemio-clinical aspects of bacterial acute infant Pneumopathies at Yalgado Ouedraogo University Health Center. Le Mali medical 25 (2010): 19-22.
  20. Review of global influenza activity, October 2016-October 2017-Bilan de l’activité grippale mondiale d’octobre 2016 à octobre 2017. Weekly Epidemiological Record 92 (2017): 761-779.
  21. Chaves CRDM, Britto JAAD, Oliveira CQD, et al. Association between nutritional status measurements and pulmonary function in children and adolescents with cystic fibrosis. Jornal Brasileiro de Pneumologia 35 (2009): 409-414.
  22. Hauschild DB, Rosa AF, Ventura JC, et al. Association of nutritional status with lung function And morbidity in children And Adolescents with cystic fibrosis: A 36-month cohort study. Rev Paul Pediatr 36 (2018): 8.
  23. Cox M, Rose L, Kalua K, et al. The prevalence and risk factors for acute respiratory infections in children aged 0-59 months in rural Malawi: A cross-sectional study. Influenza and other respiratory viruses 11 (2017): 489-496.
  24. Walker CLF, Rudan I, Liu L, et al. Global burden of childhood pneumonia and diarrhoea. The Lancet 381 (2013): 1405-1416.
  25. Wong JJ, Han WM, Sultana R, et al. Nutrition Delivery Affects Outcomes in Pediatric Acute Respiratory Distress Syndrome. Journal of Parenteral and Enteral Nutrition 41 (2017): 1007-1013.
  26. Bationo F, Ouattara BF, Zongo S, et al. Meningitis, a disease of “variations”: preventive practices and management of meningitis epidemics in Kombissiri and Réo Burkina Faso. VertigO-the electronic journal in environmental sciences 12 (2012).
  27. Gurley ES, Homaira N, Salje H, et al. Indoor exposure to particulate matter and the incidence of acute lower respiratory infections among children: A birth cohort study in urban Bangladesh. Indoor air 23 (2013): 379-386.
  28. Buchner H, Rehfuess EA. Cooking and season as risk factors for acute lower respiratory infections in African children: a cross-sectional multi-country analysis. PloS one 10 (2015).
  29. Islam F, Sarma R, Debroy A, et al. Profiling acute respiratory tract infections in children from Assam, India. Journal of global infectious diseases 5 (2013): 8-14.
  30. Acharya P, Mishra SR, Berg-Beckhoff G. Solid fuel in kitchen and acute respiratory tract infection among under five children: Evidence from Nepal demographic and health survey 2011. Journal of community health 40 (2015): 515-521.
  31. Sanbata H, Asfaw A, Kumie A. Association of biomass fuel use with acute respiratory infections among under- five children in a slum urban of Addis Ababa, Ethiopia. BMC public health 14 (2014).
  32. Ramesh BY, Manjunath N, Sanjay D, et al. Association of indoor air pollution with acute lower respiratory tract infections in children under 5 years of age. Paediatrics and international child health 32 (2012): 132-135.
  33. Mahalanabis D, Gupta S, Paul D, et al. Risk factors for pneumonia in infants and young children and the role of solid fuel for cooking: a case-control study. Epidemiology and Infection 129 (2002): 65-71.
  34. Gordon S, Gordon SB, Bruce NG, et al. Respiratory risks from household air pollution in low and middle income countries. Lancet Respir Med 2 (2014): 823-860.
  35. Taylor E, Nakai S. Prevalence of acute respiratory infections in women and children in Western Sierra Leone due to smoke from wood and charcoal stoves. International Journal of Environmental Research And Public Health 9 (2012): 2252-2265.
  36. Bruce N, Perez-Padilla R, Albalak R. The health effects of indoor air pollution exposure in developing countries. WHO Geneva (2002).
  37. Karki S, Fitzpatrick AL, Shrestha S. Risk factors for Pneumonia in Children under 5 years in a Teaching Hospital in Nepal. Kathmandu Univ Med J 12 (2014): 247-252.
  38. Mengersen K, Morawska L, Wang H, et al. The effect of housing characteristics and occupant activities on the respiratory health of women and children in Lao PDR. Science of the total environment 409 (2011): 1378-1384.
  39. Hu J, Sun X, Huang Z, et al. Streptococcus pneumoniae and Haemophilus influenzae type b carriage in Chinese children aged 12-18 months in Shanghai, China: a cross-sectional study. BMC infectious diseases 16 (2016): 149.
  40. Triche EW, Belanger K, Beckett W, et al. Infant respiratory symptoms associated with indoor heating sources. American Journal of Respiratory and Critical Care Medicine 166 (2002): 1105-1111.
  41. Yoshida LM, Nguyen HA, Watanabe K, et al. Incidence of radiologically-confirmed pneumonia and Haemophilus influenzae type b carriage before Haemophilus influenzae type b conjugate vaccine introduction in Central Vietnam. The Journal of pediatrics 163 (2013): 38-43.
     

Citation: Kafando Benoit, Savadogo Paul Windinpsidi, Millogo Tieba, Sana Adama, Sanon Sandrine, Kouanda Seni, Sondo Blaise. Exposure to Conditions of High Concentrations of Indoor Air Pollutants and Prevalence of ARIs in Children under 5 Years of Age, in Ouagadougou/Burkina Faso. Journal of Environmental Science and Public Health 3 (2019): 298-314.

Journal Statistics

Impact Factor: * 3.6

CiteScore: 2.9

Acceptance Rate: 76.49%

Time to first decision: 10.4 days

Time from article received to acceptance: 2-3 weeks

Discover More: Recent Articles

Grant Support Articles

© 2016-2024, Copyrights Fortune Journals. All Rights Reserved!