COVARIATES OF ACUTE RESPIRATORY INFECTION IN CHILDRN UNDER-FIVE: THE 2013 PHILIPPINE NATIONAL DEMOGRAPHIC AND HEALTH SURVEY
Maria Victoria C. Rodriguez 1
1 Sociology-Anthropology-Psychology Division, Department of Social Sciences, College of Arts and Sciences, University of the Philippines Los Baños
E-mail: [email protected] Received 2 June 2017
Accepted for publication 19 January 2019
Abstract
The study was conducted to determine the effects of selected socioeconomic, demographic and environmental contamination variables on the prevalence of acute respiratory infection (ARI) among Filipino children below five years old. It utilized data from the 2013 National Demographic and Health Survey (NDHS) where a total of 16,155 women aged 15-49 were interviewed. Children who were born to these women from 2008 to 2013 and are still alive during the survey period were the study cases (7,012 children). Multivariate logistic regression using Statistical Packages for the Social Sciences version 17.0 (SPSS v. 17.0) was used to determine significant risk factors related to ARI. The overall prevalence of ARI in children under five was six percent. Results show that children whose mothers are currently working are more likely to contract ARI. Furthermore, the odds of getting sick is 1.5 times higher if the child is male. Whether or not the birth of the child was wanted by the mother also emerged as a significant variable with children who are unwanted being more likely to manifest the disease. The odds of contracting ARI is almost twice for children who are 12 to 23 months old compared with those in the 48 to 59 months age group. Lastly, compared with LPG and electricity, the use of wood/charcoal and other biomass as fuel for cooking, increased the odds of contracting ARI.
Keywords: Acute Respiratory Infection (ARI), Child morbidity, 2013 National Demographic and Health Survey (NDHS), Biomass fuel
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Introduction
Acute respiratory infection (ARI) has long been a major cause of morbidity and mortality in young children and is a serious public health problem in both developed and developing countries. Pneumonia, the most serious ARI, alone kills more children than any other illness, more than AIDS, malaria and measles combined (WHO/UNICEF, 2013). About 1.4 million children under age five die of pneumonia annually which represents 18% of yearly under-five deaths worldwide (UNICEF, 2013).
The Philippines is one of the 15 countries that together account for 75% of childhood pneumonia cases worldwide (WHO, 2014).
According to the annual reports of the Department of Health (DOH), pneumonia consistently ranks as the leading cause of death in children aged 1–4 years old from 2001-2010 (DOH, 2014).
Preventing children from developing pneumonia is critical to reducing its death toll. Prevention includes many well-known child survival interventions, such as expanding vaccine coverage, promoting adequate nutrition and reducing indoor air pollution (WHO, 2014). Studies almost invariably hold that there is a relationship between socioeconomic status and levels and patterns of mortality in populations.
Thus, correlations between mortality and socioeconomic characteristics are used to generate causal inferences about mortality determinants. However, as Mosley and Chen (1984) have argued, child mortality should be studied more as a chronic disease process with multifactorial origins than as an acute, single case phenomenon.
Mortality studies could therefore be touching just a small portion of the complex child health issue. Obviously, most
children die because they are sick and so of initial and equally important concern to researchers of mortality should be the conditions that predispose children of certain mothers to states that heighten their likelihood of death (Omariba, 2001).
The relevant question then should not be why more children die, but rather why they become sick, in the first place (Rodriguez, 2008). Thus, this study sought to determine the effects of selected demographic, socioeconomic, maternal, and environmental contamination variables on the prevalence of ARI among children under five. Identification of associated risk factors of ARI may serve as a vital input in improving programs to reduce the burden of the disease. Furthermore, achieving the Sustainable Development Goal on improving health and well-being of children will depend on, to a large extent on the existing efforts to prevent and control ARI among children.
Materials and Methods Data and Sampling Design
The study obtained approval and data from ICF International for the use of the 2013 Philippine National Demographic and Health Survey (NDHS) for second stage data analysis.
The sampling scheme for the 2013 NDHS was designed to obtain representative samples for each of the 17 administrative regions of the country both in the urban and rural areas. It used a stratified two- stage sample design using the 2010 Census of Population and Housing (CPH) as frame.
The first stage consisted of a systematic selection of 800 sample enumeration areas (EA) distributed by stratum (e.g. region, urban/rural) while the second stage
involved selection of 20 sample housing from each EA using systematic random sampling (NDHS, 2013).
In the 2013 NDHS, 16,155 women aged 15- 49 were interviewed. A total of 7,012 children born to these women from 2008 to 2013 and are still alive during the survey period were the study cases. The Individual Women’s Questionnaire was used to obtain information regarding the mother’s socioeconomic background and reproductive history. A child file was created to include all relevant data for this purpose. The mother’s characteristics are the same for each of her children included in the study cases.
The prevalence of ARI was estimated by asking mothers whether their children under age five had been ill with a cough accompanied by short, rapid breathing and difficulty of breathing as a result of a problem in the chest, in the two weeks preceding the survey. While these symptoms are compatible with ARI, it should be noted that these are subjective because they are based on the mother’s perception of illness made without validation from a medical personnel (NDHS, 2013).
Conceptual Framework
The conceptual framework of this study is principally built upon the Mosley and Chen (1984) framework on child survival in developing countries which stipulates the operation of five groups of proximate determinants (i.e. socioeconomic, demographic, maternal, environmental contamination, and nutrient deficiency) on the health dynamics of a population. With the individual child as the unit of analysis, the multiple risk factors associated with ARI
morbidity in childhood is illustrated in Figure 1.
Fig 1. Conceptual Framework for the Analysis of the Determinants of Acute Respiratory Infection
Demographic Characteristics. Previous studies had shown close association between childhood ARI and demographic risk factors. For instance, most studies report a decreased odds of ARI as the age of the child increases (Harris, R. A., 2015;
Chen, Y., 2014; Bbaale, E., 2011; Tupasi, T.E., et al., 1990). This could be due to the fact that as children get older, their immune system develops and grows stronger to become better able to resist infection. On the other hand, studies also show close association between ARI and sex of the child. Although most studies show male children being more prone to ARI than their female counterparts (Rondon, A. M. P., et al., 2016; Sharma D, et al., 2013; Yaday, S., et al., 2013), others wouldshow otherwise (Chen, Y., et al., 2014). With respect to the birth order of the child, both the 1993 Philippine NDS and the 1998 NDHS revealed that children of birth order 6 or higher are more likely to have ARI as per observations during the
Acute Respiratory Infection
(ARI)
Demographic Characteristics (Age and sex of child, Birth order)
Socio-economic Characteristics (Urban-rural residence, Region, Education and current work status of
Maternal Characteristics
(Age of mother, Child ever breastfed, Child wanted)
Environmental Contamination (Smoking, Fuel used for cooking, and No. of household members)
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two weeks before the survey. While birth order greater than two are found to be significant predictors of ARI (Ohna, 1989), Jiraphongsa (1992) found birth order greater than three as a significant risk factor for ARI.
Socio-economic Characteristics. Many studies had empirically proven that socio- economic status is a powerful determinant of childhood morbidity especially in developing countries (Asghar, A., et al., 2017; Kosai, H., et al., 2015; Geberetsadik, A., et al., 2015; Goel, K., et al., 2012; Azad, 2009; Rodriguez, 2008; Tupasi, et al., 1988).
The argument here is that better socioeconomic conditions such as residence in an urban area, higher level of mother’s education, that the mother is currently working, and a relatively high economic status should lead to improved child-health status.
Maternal Characteristics. The age of the mother, breastfeeding and whether or not the mother wanted to be pregnant with respect to the reference child are the maternal factors hypothesized to have significant relationships with the occurrence of ARI. Older maternal age is associated with reduction in ARI (Rondon, A. M. P., et al., 2016; Bbaale, E., 2011). This can be attributed to the knowledge and experience concerning childcare accumulated by older women over time which gives them an edge over younger women. On the other hand, many studies have also shown breastfeeding as an important factor associated with the occurrence of diseases. It is widely recognized that children who are exclusively breastfed develop fewer infections and have less severe illnesses than those who are not. Breast milk contains the nutrients, antioxidants, hormones and antibodies needed by the
child to survive and develop, and specifically for a child’s immune system to function properly (WHO, 2006). Lastly, planned pregnancy is associated with decreased ARI (Rondon, A. M. P., et al., 2016).
Environmental Contamination. There is consistent evidence that exposure to indoor air pollution through cooking using biomass fuel (e.g. wood, charcoal, coal, agricultural residues, grass, and straw) increases the risk of ARI among children under five years old (Capuno, et al., 2018;
Ramani, V. K., et al., 2016; WHO, 2005).
Under poor ventilation conditions this can result in large exposure burdens particularly for women and their young children who usually spend most of their time in the home leaving them to higher risks of ARI.It is also discerned that cumulative incidence of ARI increase significantly with increasing cigarette smoking of family members (Tazinya, et al.
2018; Ujunwa, F., and Ezeonu, C., 2014;
Tupasi, T.E., et al., 1990). Likewise, overcrowding, which encourages the transmission of infective organismsincrease morbidity due to ARI (Asghar, A., et al., 2017; Ujunwa, F., and Ezeonu, C., 2014;
Prajapati B., et al., 2012; Tupasi, T.E., et al., 1990).As household size increases, the number of potential interactions between infected and susceptible individuals also increases.
Method of Analysis
The dependent variable (whether a child had ARI or not in the two weeks before the survey period) is dichotomous with a highly skewed distribution. Logistic regression is thus, used to identify which of the hypothesized independent variables is significantly related to ARI. The logistic regression model which was fitted to the data is as follows:
Logit P = Ln (P/1-P) = a + b1X1 + b2X2 … + biXi where:
P = the probability of the reference child having had ARI, (1-P) = the probability of the reference child not having had ARI
a = intercept
b1, b2,…, bi = regression coefficients, X1, X2,…, Xi = explanatory or control variables included in the model.
It must be noted that logistic regression models are commonly estimated by the maximum likelihood method and are interpreted in terms of odds ratios. Thus, it is the measure of the odds or chances that a woman’s child contracted ARI as indicated by the independent variables.
For variables with more than one category, a reference category is assigned and the odds of contracting ARI are interpreted relative to that category. Ratios lower than one signify a reduced odds of ARI morbidity in that category compared to the reference category, while ratios greater than one indicate a greater odds compared to the reference category.
Data was analyzed using Statistical Package for the Social Sciences version 17.0 (SPSS v.
17.0).
Results and Discussion Differentials in ARI
Demographic Factors
Table 1 shows that the prevalence of ARI is lowest among children below six months old (3.4%) and highest among the 12-23 months old (7.6%) with the rate decreasing from then on as the child gets older. This is consistent with most studies from developed and developing countries which found that the proportion of ARIs is lowest during the first six months of life, increases and reaches its peak below 36 months then decreases with increasing age of the child
(El-Abd Ahmed A., 2016; Ujunwa FA and Ezeonu CT, 2014; Montasser N, et al., 2012). It can be noted that the increasing prevalence rate falls within the age of introduction of complementary foods, decreasing breast feeding with its attendant risks and the waning of passive maternal immunity.
A marked difference in ARI prevalence is observed between boys and girls with the former being more predisposed to the disease than the latter (6.5% vs. 4.9%). On the other hand, an increasing prevalence rate was observed with increasing birth order with the eldest child having the lowest rate at 4.6% and those belonging to birth orders 4 and above, the highest at 6.2%.
Socioeconomic Factors
Symptoms of ARI are more often reported for children living in the rural areas than in the urban areas (6.2% vs. 5%). There is marked variation in ARI among the major island groups, with children in the Visayas having the highest prevalence rate (8.6%), followed by rest of Luzon (5.4%), while those in the National Capital Region (4.8%) showed the lowest rate.
In general, ARI prevalence is higher among children born to mothers with lower education (6.3%) compared with those whose mothers have reached secondary (5.4%) and higher education (5.7%).
Moreover, ARI is more common in children whose mothers are currently working during the time of the survey. Meanwhile, a decreased prevalence rate is observed in children belonging to the last two wealth index quintiles (e.g. richer and richest) compared with those in the first three quintiles (e.g. poorest, poorer, and middle).
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Table 1. Prevalence of Acute Respiratory Infection among 7,012 children under age five by demographic and socioeconomic characteristics, Philippines 2013 NDHS.
Variable Percent Number of children
Demographic Characteristics
Age of child
Under 6 months 3.4 672
6-11 months 6.5 733
12-23 months 7.6 1,423
24-35 months 6.2 1,330
36-47 months 5.0 1,458
48-59 months Sex
4.7 1,396
Male 6.5 3,636
Female 4.9 3,376
Birth Order
1 4.6 2,106
2 –3 6.1 2,857
4 and above 6.2 2,049
Socioeconomic Characteristics Place of Residence
Urban 5.0 2,865
Rural 6.2 4,147
Region
NCR 4.8 774
Rest of Luzon 5.4 2,727
Visayas 8.6 1,141
Mindanao 5.0 2,370
Education of Mother
No education 6.2 146
Primary 6.3 1,582
Secondary 5.4 3,436
Higher Work Status of Mother
5.7 1,848
Currently working 6.4 2,716
Not working 5.3 4,271
Wealth Index
Poorest 6.1 2,190
Poorer 5.7 1,575
Middle 6.7 1,334
Richer 4.8 1,095
Richest 4.3 818
TOTAL 5.7 7,012
Table 2. Prevalence of Acute Respiratory Infection among 7,012 children under five by maternal characteristic and environmental contamination, Philippines 2013 NDHS.
Variable Percent Number of children
Maternal characteristics Age of mother
15 – 19 7.1 269
20 – 24 6.0 1,585
25 – 29 5.7 1,765
30 – 34 5.9 1,552
35 – 39 4.5 1,101
40 – 44 5.8 550
45 – 49 6.3 190
Child ever breastfed
Yes 5.9 6,486
No 3.8 500
Child Wanted
Yes 5.0 5,072
No 7.5 1,932
Environmental Contamination Mother does not smoke
Yes 5.7 6,545
No 6.0 467
Fuel Used for Cooking
Electricity, LPG, natural gas 4.2 1,803
Wood, charcoal, other biomass 6.2 5,025
No. of household members
1-4 members 5.5 1,584
5-6 members 5.3 2,535
7 and above 6.2 2,893
TOTAL 5.7 7,012
Table 3. Odds Ratios of Full and Reduced Models on ARI Prevalence by selected variables, 7,012 children under age five, Philippines, 2013 NDHS.
Variables Full Model Reduced Model
A. Demographic Variables
Age of child (vs. 48-59 months old)
< 6 months 0.72 0.72
6 – 11 months 1.39 1.40
12 – 23 months 1.63** 1.65**
24 – 35 months 1.30 1.32
36 – 47 months 1.06 1.07
Sex (vs. Female) 1.38** 1.38**
Birth Order (vs. 4 and above)
1 0.85
2-3 1.09
B. Socioeconomic Variables Region (vs. NCR)
Rest of Luzon 1.03 1.03
Visayas 1.60* 1.60*
Mindanao 0.92 0.92
Maternal work status (vs. Working) 0.80* 0.80*
Wealth Index (vs. Richest Quintile)
Poorest 1.53* 1.58*
Poorer 1.36 1.38
Middle 1.57* 1.58*
Richer 1.18 1.18
C. Maternal Characteristics
Birth Wanted by Mother (vs. Yes) 1.45** 1.46**
** p < 0.01 * p < 0.05
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88 Maternal Factors and Environmental Contamination
Children born to mothers aged 15-19 years old exhibit the highest prevalence of ARI at 7.1% while those of mothers 35-39 years old have the lowest prevalence rate at 4.5%
(Table 2). A regular pattern showing any relationship between ARI and age of the mother, however, was not born out of the data. Children who are breastfed are more likely to suffer from ARI than those not breastfed. This is consistent with the findings of Alcantara, et al (2000) and Rodriguez (2008)where the unexpected pattern may be explained by “ever breastfed” as being a very crude measure of the breastfeeding variable because the duration of breastfeeding has no time reference in this case, hence, it is very difficult to establish its direct causality on ARI.On the other hand, children whose births are wanted by their mothers are less likely to contract the disease compared to their counterparts whose births were wanted later on or were not wanted at all (5% vs. 7.5%).
With regard to environmental factors, children whose mothers do smoke tobacco have slightly higher rates of reported prevalence of ARI compared to those who do not (6% vs. 5.7%). Similarly, a higher ARI morbidity was exhibited by children in households who used wood, charcoal and other biomass as fuel for cooking (6.2%) than those who used electricity and liquefied petroleum gas (4.2%). The number of household members may indicate susceptibility to ARI through contamination by an infected person. The lowest prevalence was observed in households consisting of 5-6 members
(5.3%) and the highest, with seven or more members (6.2%).
Multivariate Analysis
Using binary logistic regression, only independent variables that showed significant relationship when taken singly with ARI were included in the multivariate logistic regression (full model) to prevent unstable estimates. However, only those variables showing significant relationship with ARI in the full model were then considered in the reduced model. This strategy is expected to produce the simplest and most parsimonious model that would explain ARI prevalence. Thus, for instance, variables such as mother’s education, her age, smoking status, and number of household members, though they singly showed to have significant relationships with ARI were dropped from the full model and consequently, were not included in the reduced model.
Controlling for the effects of other predictors, the odds of contracting ARI is almost twice for children who are 12 to 23 months old compared with children in the 48 to 59 months age group. Except for the less than six months age group, all the other age groups showed increased odds of ARI although the association fails to show statistical significance (Table 3).
There is a significant gender effect in accounting for patterns of ARI morbidity where the chances of reporting for ARI is almost 1.5 times higher for boys than for girls.However, the birth order of a child is not a significant determinant of susceptibility to ARI.
89 Results also show regional differentials in ARI morbidity where the odds of contracting the illness is 1.6 times higher in the Visayas than in the National Capital Region.
A statistically significant association between ARI and mother’s work status is borne out by the data where the odds of contracting ARI is decreased by 22% for children whose mothers are not working compared to those who are employed.
Similarly, the wealth status of the household has significant effect on ARI prevalence when controlling for the effect of the other predictors. Children belonging to the poorest and middle wealth categories are 1.5 times more susceptible to ARI than those in the richest quintile. On the other hand, a child who is either not wanted at the time of birth, or whose birth was wanted later on, or not at all, has 1.5 times more chances of contracting ARI compared with a child whose birth was wanted by the mother.
Conclusion and Recommendations This study sought to determine the effects of selected socioeconomic, demographic, maternal and environmental factors to morbidity due to acute respiratory using the 2013 Philippine National Demographic and Health Survey.
Results of the study show that on the average, children whose births were unplanned are more susceptible to acute respiratory infection than their intended peers. Reducing the number of unintended births, therefore, can help lessen the burden of ARI and improve the health and wellbeing of the child in general. The
findings therefore, argue for enhanced focus on family planning to reduce the prevalence of unintended pregnancy especially that nearly 18 percent of currently married women in the country were reported to have an unmet need for family planning (NDHS, 2013). This is also consistent with the post-Cairo justification for family planning which asserts that lower fertility, including fewer unwanted babies, leads to better health outcomes. In the light of the premise that every child should be a wanted child, policy measures to promote reproductive health should be continued and strengthened with emphasis on family planning.
Children whose mothers are working face a higher likelihood of morbidity due to ARI.
Conceptually, the work status of women can affect child health because a working woman has less time to devote to child care. While being employed may translate to better economic and health conditions, children whose mothers are working are usually left to the care of another sibling or housemaid leaving the child neglected altogether.
The results of the study, in general, imply government policy efforts in line with poverty alleviation. Since the socioeconomic status was computed through a combination of ownership of consumer items and items reflective of the living conditions of the households, the results suggest the need for increasing the purchasing power of the populace and finding ways to improve facilities related to sanitation (e.g. toilet facilities and drinking
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90 water) and the general living conditions of the household.
The need to address regional disparities is also clearly implied. Regions outside of NCR who are more underprivileged in terms of child health care services may need special attention. Closer health surveillance and monitoring by the Department of Health to ensure that delivery of health services reaches even those areas outside of Metro Manila are called for. Succeeding studies could also be done on a smaller geographical scale such as on a per region basis. Each region has its own set of demographic, socioeconomic and proximate determinants of child survival unique to each region. More meaningful and conclusive results specific to each region could be drawn from such studies.
On the whole, there is a need to address inequities and set mechanisms to target the poor. The financial burden of paying for services is a major obstacle to the poor’s access to health care and can make them even poorer. Wealthier families enjoy a higher quality of service in terms ofbetter facilities while the poor may forgo health care altogether.
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