|
 
 |
| ORIGINAL ARTICLE |
|
| Year : 2021 | Volume
: 12
| Issue : 1 | Page : 99 |
|
Family health behavior: Preventive measures against acute respiratory infections in under-5 children
Mardiana Dwi Puspitasari, Mugia Bayu Rahardja
Center for Research and Development, National Population and Family Planning Board (BKKBN), Jakarta, Indonesia
| Date of Submission | 27-Sep-2020 |
| Date of Acceptance | 21-Jan-2021 |
| Date of Web Publication | 30-Jul-2021 |
Correspondence Address:
Mardiana Dwi Puspitasari
Center for Research and Development, National Population and Family Planning Board (BKKBN), Jl. Permata no. 1, Halim Perdanakusuma, Jakarta Timur
Indonesia
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/ijpvm.IJPVM_580_20
Background: The under-5 mortality rate in Indonesia is 32 per 1,000 live births, still higher than the SDG target. Acute respiratory infections (ARIs), as one of the leading causes of death, must be prevented. Arguments emerge concerning the association of home crowding, health behavior, and the incidence of ARI. Methods: A cross-section analysis with the Indonesia Demographic and Health Survey (IDHS) 2017 dataset is performed. Samples are restricted to 16,555 children aged 0–59 months who lived with their mother (eligible women interviewed) during the survey. For each of the variables observed during this study, missing data must be omitted as exclusion criteria. A 100 per cent answer rate was achieved. Logistic regression was used to determine ARI-associated factors, by examining the effect of each explanatory factor (independent variables) on the odds ratio of ARI (one dependent binary variable). Results: The prevalence of ARI was more common among children living in the poorest households (AOR 1.66; 95% CI, 1.20 – 2.28) and those exposed to indoor tobacco smoke pollution (AOR 1.27; 95% CI, 1.04–1.56). On the other hand, those aged 0–5 months (AOR 0.59; 95% CI, 0.43–0.82), living at home with improved sanitation (AOR 0.74; 95% CI, 0.61–0.89), and exclusively breastfed (AOR 0.85; 95% CI, 0.73–0.99) were less likely to have ARI. Conclusions: Home crowding is not associated with ARI. Efforts should be focused on preserving family health behavior. The family functioned as a health-support system for their under-5 children by establishing an indoor tobacco smoking-free zone, practicing exclusive breastfeeding, and enhancing hygiene facilities.
Keywords: Breastfeeding, crowding, family health, tobacco smoke pollution
How to cite this article:
Puspitasari MD, Rahardja MB. Family health behavior: Preventive measures against acute respiratory infections in under-5 children. Int J Prev Med 2021;12:99 |
How to cite this URL:
Puspitasari MD, Rahardja MB. Family health behavior: Preventive measures against acute respiratory infections in under-5 children. Int J Prev Med [serial online] 2021 [cited 2023 Sep 27];12:99. Available from: https://www.ijpvmjournal.net/text.asp?2021/12/1/99/322849 |
| Introduction | |  |
Pneumonia, a serious type of acute respiratory infection (ARI) that directly affects the lungs, is the leading cause of death in children under-5 worldwide.[1],[2] Indonesia is one of the 15 countries with the highest burden of pneumonia deaths among children under-5.[3] Data showed that Indonesia's under-5 mortality rate was 32 per 1,000 live births which was still higher than the 2030 SDGs target.[4]
There are some literature debates in evidence that focus on the incidence and associated factors of ARI in children under-5 years of age. Previous studies reported the association between home crowding and children with ARI.[5],[6],[7],[8],[9] Housings that lack sufficient living area may have a direct adverse health impact on children, as the lack of personal space may lead to the transfer of infection-based illness from one household member to another. On the other hand, it has been reported that the relationship between housing and health has not been completely clarified.[10] Health behaviors should be a link between housing and health.[10],[11],[12] In addition, another study identified a negligible association between housing conditions and ARI.[13]
Based on Bronfenbrenner's ecological system theory, a family should be included as a family health-care system and its members.[14] As for children who spend a significant amount of time indoors, the family is their primary environment. The McMaster model of family functioning strongly encourages the development of the family and its members together by performing a set of family activities, including the preservation of healthy behavior to complete family function.[15],[16]
Evidence has shown that health-related family activities, such as tobacco smoking and exclusive breastfeeding, are associated with the incidence of ARI in children under-5 years of age. Indoor exposure to tobacco smoke pollution was prevalent in Indonesian housing with just around 28% of households enforcing a tobacco smoking-free home rule.[4] However, studies have reported that tobacco smoke pollution has adversely affected children's respiratory health.[17],[18],[19] The tobacco smoking-free zone was required to mitigate the risk of respiratory infection in children.[20] Furthermore, exclusive breastfeeding until 6 months of age played a beneficial role in minimizing the risk of children suffering from ARI.[21],[22],[23]
Considering some controversy, the present study aims to examine the incidence of ARI in Indonesian children under-5 years of age with its associated factors.
| Methods | | |
Data and participants
The current dataset comes from the 2017 Indonesia Demographic and Health Survey (IDHS),[24] a national survey conducted in 34 provinces. A two-stage stratified sampling design was drawn from the 2010 Population Census. The first stage involves a systematic sampling proportional to the size (PPS) of the set of 1,970 census blocks and the second is a random selection of 25 ordinary households from each of the selected census blocks. Totally, 49,261 households were sampled. The IDHS 2017 has a response rate of 99.5% for the household interviewed (47,963). Of the 47,963 households interviewed, 50,730 women were eligible, but only 49,627 eligible women were interviewed (97.8%).
This present study is limited to children under 5 years of age who resided with their mother (eligible women interviewed) during the survey. There are 16,555 children under 5 years of age recorded in 2017 IDHS. For each of the variables observed in this study, we do not find missing data that must be excluded as exclusion criteria in this analysis. Therefore, the final sample consisted of 16,555 children aged between 0 and 59 months (100% response rate). Data is obtained through direct interviews with women's questionnaires administered to eligible women interviewed with respect to their most recent children born in the last five years before the survey.
Variables
- Child health status
Child health status is divided into two groups of participants in this study. The first group is children aged 0–59 months with ARI and the second group is otherwise. The DHS-7 guide identifies children with ARI as children under-5 years of age who had cough, accompanied by short, rapid, and/or difficult breathing, two weeks preceding the survey.[25] Questions on child health status were administered to the mother. - Sociodemographic characteristics
The sociodemographic predictors include individual children, household, and environmental characteristics in our study. A child's age is listed as 0–5, 6–23, and 24–59 months of age. The household wealth index describes household characteristics and lists them as the poorest, poor, middle, rich, and the richest. The household wealth index is calculated on the basis of the household ownership of assets and facilities. The DHS standardized each household score for each asset and then established the factor score using principal components analysis to classify the wealth quintiles into five categories. Environmental predictors include the region and the place of residence. Previous research recorded zone based on the basis of ambient air quality and community activities to determine its association with the incidence of ARI.[26],[27],[28] Java island is a heavily populated area, while the outer island is not.[29] Therefore, the region is classified as the island of Java and the outer islands. The place of residence is listed as urban and rural areas. - Housing characteristics
Housing amenities include water supply, sanitation, and crowding. The UN Habitat is used to define the variables listed above.[8],[30] A household was deemed to have access to the improved water supply if it had access to protected water from outside contamination at a distance of 7 meters or more to the nearest septic tank and garbage disposal for cooking and washing, and bottled water/refilled water for drinking. Improved sanitation facilities were defined as a household with a private toilet and a septic tank. UN-Habitat defines home crowding as more than three persons per bedroom. However, because of the intent of our study which is tailored to family characteristics, such as relationship status, we used a norm of up to two people per bedroom. - Family Health behavior
Taking into account the family functioning, this study uses indoor exposure to tobacco smoke pollution and breastfeeding as family health behaviors. Tobacco smoke pollution exposure is categorized as a tobacco smoking-free home zone and otherwise. The DHS-7 guide describes exclusive breastfeeding as infants between 0–6 months of age who are exclusively breastfed without receiving complimentary food.[25]
Analysis
The data is analyzed in two phases. First, a descriptive analysis is used to display the distribution of children aged 0–59 months according to the explanatory variables and the ARI status of these children. The proportion of children under-5 who suffered from ARI is recorded in percentages as a result of the Chi-square test. The Chi-square test is performed to assess the significant correlation between ARI and each explanatory variable.[31]
Second, the likelihood ratio test and Wald test are used in a multivariate logistic regression analysis. Multivariate logistic regression analysis of ARI-associated determinants is performed. All predictors are included in the model, following the integrated model.[2] Dependent binary variable meets the Bernoulli distribution[32] as seen in the formula:
The likelihood ratio is used to calculate the effect of all independent variables on the dependent variable of the model, using the G formula as follows:
The G formula follows a Chi-square distribution with a degree of freedom (p-value) in such a way that the hypothesis is rejected if P value <α is used, which implies that the independent variables jointly influence the dependent variable.
The Wald test is used to partially measure the effect of each independent variable on the dependent variable. The analysis compares the Wald test statistical value to the Chi-square value. The statistical formula for the Wald test is as follows:
The hypothesis is dismissed if P value <α is used, which means that the independent variables partially affect the dependent variable. The odds ratio (OR) along with 95% confidence intervals (CI) is used to calculate association.
Ethical consideration
The IDHS 2017 data collection was downloaded from the DHS website in compliance with the Access Policy (https://microdata.worldbank.org/index.php/catalog/3477). The procedures and questionnaires for 2017 IDHS are in accordance with the Standard DHS survey protocol approved by the ICF Institutional Review Board (IRB) and conform with the U.S. Department of Health and Human Services regulations for the Protection of Human Subjects (45 CFR 46) (https://dhsprogram.com/methodology/Protecting-the-Privacy-of-DHS-Survey-Respondents.cfm).
| Results | | |
Sociodemographic characteristics and correlation test
Of the 16,555 children under-5 years of age who were living with their mother, 693 children had ARI.
[Table 1] provides the demographic distribution of under-5 children. The descriptive analysis shows an almost equal distribution of children by region, place of residence, household wealth index, bedroom dwelling, and breastfeeding practice. The majority (86.7%) of under-5 children lived in houses with improved water supply. About 74.4% of children lived in houses with improved sanitation, while only around 25.6% of children lived in households without improved sanitation. Approximately, 76.3% of children were exposed to indoor tobacco smoke pollution, while only 23.7% of children were living in a tobacco smoking-free household. The majority (60.1%) of children were aged 24–59 months, whereas 30.4% and 9.5% were aged 6–23 months and 0–5 months, respectively. | Table l: Sociodemographic characteristics and Correlation test of under-5 children according to ARI status, Indonesia 2017
Click here to view |
The Chi-square test shows that the place of residence, household wealth index, bedroom dwelling, improved water supply, improved sanitation, tobacco smoke pollution, and child age are significantly correlated with ARI in children under-5 years of age (P-value <0.05).
In the final model with adjustment for other variables [Table 2], children aged 0–5 months were 1.69 times less likely to be at risk for ARI compared to those aged 24–59 months. Based on the economic status, children living in the poorest households had the highest odds of being infected (AOR 1.66; 95% CI, 1.20–2.28). Children living at home with improved sanitation were 1.35 times more likely to reduce ARI than those living at home with unimproved sanitation. Concerning family health behavior, children exposed to tobacco smoke pollution at home had higher odds of developing ARI (AOR 1.27; 95% CI, 1.04 – 1.56) than those living in a tobacco smoking-free household. Children who were exclusively breastfed were 1.17 times more likely to experience ARI than those who were not. | Table 2: Logistic regression model for the predictors of under-5 children with ARI status, Indonesia (n=16,555)
Click here to view |
| Discussion | | |
The present study clarifies the association between home crowding and the prevalence of ARI in children under-5 years of age. Findings indicate that home crowding has been reported to no longer be taken into account in children's health following changes in demographic and socioeconomic determinants.[12] In contrast, indoor exposure to tobacco smoke pollution[17],[19] and the practice of exclusive breastfeeding[33],[34] are significantly associated with ARI. Thus family acts as a health-support system for its members.[35]
Some factors, such as improved household sanitation,[36],[37] younger age, and higher economic status, are associated with a decrease in the risk of under-5 children suffering from ARI. As age increased, the children are more likely to develop ARI. The explanation may be due to complementary feeding practices that need to be followed by the family as the child was growing up from 6 months of age.[38],[39] The IDHS 2017 found that only around 40% of young children aged 6–23 months had sufficient infant and young child feeding practice.[4] IDHS 2012 also reported high prevalence of smoking in poor families in Indonesia.[40]
On the other hand, improved water supply is not significantly associated with ARI in children under-5 years of age. This finding is in contrast to a study on the need for in-home piped water, which is unlikely to be contaminated by the virus to reduce the risk of infection.[41] Contaminated bottled water has been found in some areas of Indonesia.[42] Our result is likely as there is a lack of control over the hygiene of the refilled drinking water source in Indonesia as one of the metrics for improved water supply in the DHS measure.
The region and the place of residence are statistically insignificant. Controversy on the results of previous studies relates to the association of children living in urban or rural areas at risk of acute respiratory infection.[43],[44],[45],[46] The impact of regional heterogeneity on the risk of ARI in children cannot also be explained as a high prevalence of tobacco smoking in most regions of Indonesia.[47]
The strength of this study is the large nationally representative data that make it possible to generalize the results to the national level. However, the data on ARI status relies on retrospective information provided by mothers which might be subject to revocation bias. It is also difficult to assert a cause-and-effect relationship. The cross-section design analysis does not determine the causality of variables, but only calculate the association of the variables.
| Conclusions | | |
This cross-section analysis shows that home crowding is not associated with the risk of acute respiratory infection in children under-5 years of age after consideration of other factors. The findings suggested that the role of the family as the primary environment is to support their under-5 children by maintaining a tobacco smoking-free zone at home and by breastfeeding exclusively up to 6 months of age. In addition, improved household sanitation must be ensured to prevent children from contracting ARI. Evidence can be used in particular to motivate families to preserve family health behavior in support of child health promotion.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | United Nations Inter-agency Group for Child Mortality Estimation (UN IGME). Levels & Trends in Child Mortality: Report 2019, Estimates developed by the United Nations Inter-agency Group for Child Mortality Estimation. New York: 2019.  |
| 2. | UNICEF, WHO. Pneumonia: The Forgotten Killer of Children. New York: UNICEF; 2006. |
| 3. | International Vaccine Access Center (IVAC). Pneumonia and Diarrhea Progress Report 2020. Johns Hopkins Bloomberg School of Public Health; 2020. |
| 4. | National Population and Family Planning Board (BKKBN), Statistics Indonesia (BPS), Ministry of Health (Kemenkes), ICF. Indonesia Demographic and Health Survey 2017. Jakarta, Indonesia: BKKBN, BPS, Kemenkes, and ICF; 2018. |
| 5. | Cox M, Rose L, Kalua K, de Wildt G, Bailey R, Hart J. The prevalence and risk factors for acute respiratory infections in children aged 0-59 months in rural Malawi: A cross-sectional study. Influenza Other Respi Viruses 2017;11:489-96. |
| 6. | Firdaus G, Ahmad A. Relationship between housing and health: A cross-sectional study of an urban centre of India. Indoor Built Environ 2013;22:498-507. |
| 7. | Lobato-Cordero A, Quentin E, Lobato-Cordero G. Spatiotemporal analysis of influenza morbidity and its association with climatic and housing conditions in ecuador. J Environ Public Health 2019;2019:6741202. |
| 8. | Nkosi V, Haman T, Naicker N, Mathee A. Overcrowding and health in two impoverished suburbs of Johannesburg, South Africa. BMC Public Health 2019;19:1-8. |
| 9. | Tse SM, Weiler H, Kovesi T. Food insecurity, vitamin D insufficiency and respiratory infections among inuit children. Int J Circumpolar Health 2016;75:29954. |
| 10. | Swope CB, Hernández D. Housing as a determinant of health equity: A conceptual model. Soc Sci Med 2019;243:112571. |
| 11. | Herrin WE, Amaral MM, Balihuta AM. The relationships between housing quality and occupant health in Uganda. Soc Sci Med 2013;81:115-22. |
| 12. | Kohen DE, Bougie E, Guèvremont A. Housing and health among Inuit children. Heal Reports 2015;26:21-7. |
| 13. | Tustingid LS, Gething PW, Gibsonid HS, Greenwoodid B, Knudsenid J, Lindsayid SW, et al. Housing and child health in sub-Saharan Africa: A cross-sectional analysis. PLoS Med 2020;17:e1003055. |
| 14. | Pratt KJ, Sonney JT. Family science and family-based research in integrated and health care contexts: Future considerations for families, systems, & health. Fam Syst Health 2020;38:1-5. |
| 15. | Dai L, Wang L. Review of family functioning. Open J Soc Sci 2015;3:134-41. |
| 16. | Miller IW, Ryan CE, Keitner GI, Bishop DS, Epstein NB. The McMaster approach to families: Theory, assessment, treatment and research. J Fam Ther 2000;22:168-89. |
| 17. | Jones LL, Hashim A, McKeever T, Cook DG, Britton J, Leonardi-Bee J. Parental and household smoking and the increased risk of bronchitis, bronchiolitis and other lower respiratory infections in infancy: Systematic review and meta-analysis. Respir Res 2011;12:1-11. |
| 18. | Miyahara R, Takahashi K, Anh NTH, Thiem VD, Suzuki M, Yoshino H, et al. Exposure to paternal tobacco smoking increased child hospitalization for lower respiratory infections but not for other diseases in Vietnam. Sci Rep 2017;7:1-7. |
| 19. | Zhuge Y, Qian H, Zheng X, Huang C, Zhang Y, Li B, et al. Effects of parental smoking and indoor tobacco smoke exposure on respiratory outcomes in children. Sci Rep 2020;10:1-9. |
| 20. | Been J V., Millett C, Lee JT, Van Schayck CP, Sheikh A. Smoke-free legislation and childhood hospitalisations for respiratory tract infections. Eur Respir J 2015;46:697-706. |
| 21. | Ahmed KY, Page A, Arora A, Ogbo FA, Agho KE, Diallo T, et al. Associations between infant and young child feeding practices and acute respiratory infection and diarrhoea in Ethiopia: A propensity score matching approach. PLoS One 2020;15:1-20. |
| 22. | Khan J, Vesel L, Bahl R, Martines JC. Timing of breastfeeding initiation and exclusivity of breastfeeding during the first month of life: Effects on neonatal mortality and morbidity—A systematic review and meta-analysis. Matern Child Health J 2015;19:468-79. |
| 23. | Saeed OB, Haile ZT, Chertok IA. Association between exclusive breastfeeding and infant health outcomes in Pakistan. J Pediatr Nurs 2020;50:e62-8. |
| 24. | National Population and Family Planning Board (BKKBN) [Government of Indonesia], Statistics Indonesia (BPS) [Government of Indonesia], Ministry of Health (Kemenkes) [Government of Indonesia]. Indonesia Demographic and Health Survey (IDHS) 2017 [Dataset]. IDN_2017_DHS_v01_M2017. Available from: http://www.dhsprogram.com/[Last accessed on 2019 Dec 7]. |
| 25. | ICF. Demographic and Health Surveys Standard: Recode Manual for DHS 7. In: The Demographic and Health Surveys Program. Rockville, Maryland, USA: ICF; 2018. |
| 26. | Adesanya OA, Chiao C. A multilevel analysis of lifestyle variations in symptoms of acute respiratory infection among young children under five in Nigeria. BMC Public Health 2016;16:1-12. |
| 27. | Amsalu ET, Akalu TY, Gelaye KA. Spatial distribution and determinants of acute respiratory infection among under-five children in Ethiopia: Ethiopian demographic Health Survey 2016. PLoS One 2019;14:45-59. |
| 28. | Chiao C, Deji-Abiodun O. A global analysis of the regional variation in the symptoms of acute respiratory infection during childhood: Epidemics and their association with environmental vulnerability. Heal Place 2020;65:102400. |
| 29. | Statistics Indonesia (BPS). Statistik 70 Tahun Indonesia Merdeka. Jakarta, Indonesia: Badan Pusat Statistik; 2015. |
| 30. | Armah FA, Ekumah B, Yawson DO, Odoi JO, Afitiri AR, Nyieku FE. Access to improved water and sanitation in sub-Saharan Africa in a quarter century. Heliyon 2018;4:e00931. |
| 31. | Agresti A. Categorical Data Analysis. USA: John Wiley & Sons; 1990. |
| 32. | Hosmer DW, Lemeshow S. Applied Logistic Regression. 2 nd ed. USA: John Wiley & Sons, Inc; 2000. |
| 33. | Dong G-H, Qian Z, Liu M-M, Wang D, Ren W-H, Bawa S, et al. Breastfeeding as a modifier of the respiratory effects of air pollution in children. Epidemiology 2013;24:387-94. |
| 34. | Zielinska MA, Hamulka J. Protective effect of breastfeeding on the adverse health effects induced by air pollution: Current evidence and possible mechanisms. Int J Environ Res Public Health 2019;16:1-29. |
| 35. | Barnes MD, Hanson CL, Novilla LB, Magnusson BM, Crandall AC, Bradford G. Family-centered health promotion: Perspectives for engaging families and achieving better health outcomes. Inq J Heal Care Organ 2020;57:46958020923537. |
| 36. | Seidu AA, Dickson KS, Ahinkorah BO, Amu H, Darteh EKM, Kumi-Kyereme A. Prevalence and determinants of acute lower respiratory infections among children under-five years in sub–Saharan Africa: Evidence from demographic and health surveys. SSM-Popul Heal 2019;8:100443. |
| 37. | Ullah MB, Mridha MK, Arnold CD, Matias SL, Khan MSA, Siddiqui Z, et al. Factors associated with diarrhea and acute respiratory infection in children under two years of age in rural Bangladesh. BMC Pediatr 2019;19:1-11. |
| 38. | Debnath SC, Haque ME, Hasan DMM, Samin S, Rouf MA, Rabby MF. Undernutrition and morbidity profile of exclusively breastfeeding children: A cross-sectional study. Int J Prev Med 2018;9:55. [ PUBMED] [Full text] |
| 39. | Malekzadeh J, Synai S, Ebrahimzadeh Koor B, Falsafian G, Nakhaie M. Growth indices of exclusively breastfed until 6 months age and formula-fed infants in southwest of Iran. Int J Prev Med 2019;10:207. [ PUBMED] [Full text] |
| 40. | Herawati P, Afriandi I, Wahyudi K. Determinan Paparan Asap Rokok di Dalam Rumah: Analisis Data Survei Demografi dan Kesehatan Indonesia (SDKI) 2012. Buletin Penelitian Kesehatan. Buletin Penelitian Kesehatan 2019;47:245-52. |
| 41. | Thomas TK, Ritter T, Bruden D, Bruce M, Byrd K, Goldberger R, et al. Impact of providing in-home water service on the rates of infectious diseases: Results from four communities in Western Alaska. J Water Health 2016;14:132-41. |
| 42. | Irda Sari SY, Sunjaya DK, Shimizu-Furusawa H, Watanabe C, Raksanagara AS. Water sources quality in urban slum settlement along the contaminated river basin in Indonesia: Application of quantitative microbial risk assessment. J Environ Public Health 2018;2018:1-7. |
| 43. | Krishnan D, Omprakash A, Ramaswamy P, G T, S S, Balakrishnan K. Prevalence of acute respiratory infection in children less than 2 years in rural and urban population in and around Chennai, Tamil Nadu. Natl J Physiol Pharm Pharmacol 2019;9:804-808. |
| 44. | Sharma D, Kuppusamy K, Bhoorasamy A. Prevalence of acute respiratory infections (ARI) and their determinants in under five children in urban and rural areas of Kancheepuram District, South India. Ann Trop Med Public Heal 2013;6:513-8. |
| 45. | Brugha R, Grigg J. Urban air pollution and respiratory infections. Paediatr Respir Rev 2014;15:194-9. |
| 46. | Rahman SRA, Ismail SNS, Sahani M, Ramli MF, Latif MT. A case crossover analysis of primary air pollutants association on acute respiratory infection (ARI) among children in urban region of Klang valley, Malaysia. Ann Trop Med Public Heal 2017;10:1587-90. |
| 47. | Hapsari D, Nainggolan O, Kusuma D. Hotspots and regional variation in smoking prevalence among 514 districts in Indonesia: Analysis of basic health research 2018. Glob J Health Sci 2020;12:1-32. |
[Table 1], [Table 2]
|
Search Pubmed for