The prevalence and risk factors for acute respiratory infections in children aged 0-59 months in rural Malawi: A cross-sectional study

Background: Acute Respiratory Infections (ARI) are a leading cause of childhood mortality and morbidity. Malawi has high childhood mortality but limited data on the prevalence of disease in the community. Methods: A cross-sectional study of children aged 0-59 months. Health passports were examined for ARI diagnoses in the preceding 12 months. Children were physically examined for malnutrition or current ARI. Results: 828 children participated. The annual prevalence of ARI was 32.6% (95% CI 29.3-36.0%). Having a sibling with ARI (OR 1.44, P =.01), increasing household density (OR 2.17, P =.02) and acute malnutrition (OR 1.69, P =.01) were predictors of infection in the last year. The point prevalence of ARI was 8.3% (95% CI 6.8-10.4%). Risk factors for current ARI were acute-on-chronic malnutrition (OR 3.06, P =.02), increasing household density (OR1.19, P =.05) and having a sibling with ARI (OR 2.30, P =.02). Conclusion: This study provides novel data on the high prevalence of ARI in Malawi. This baseline data can be used in the monitoring and planning of future interventions in this population. This was a cross‐sectional, population‐based study of a random sample of children aged 0‐59 months in rural Monkey Bay. Data were obtained in three ways: an oral survey, physical examination and inspection of health passports. Malawi is divided into 28 administrative districts. Mangochi district, with an estimated population of 600 000, has lower income and poorer health than average.25 Mangochi is divided into five healthcare zones, one of which is Monkey Bay. Our study population included all children aged 0‐59 months living in rural Monkey Bay. Within areas, health surveillance assistants (HSAs) provide basic health assessments26 and refer children with symptoms of respiratory disease to healthcare providers. Communities were defined as the area under one HSA. Some HSAs oversee multiple villages. Rural communities, with an estimated population of less than 2000 and no trading post, were eligible for inclusion. Within a community, all children aged 0‐59 months were eligible for inclusion in the study provided their parent/guardian consented and the household was registered on a pre‐study census conducted in November 2014 as part of a larger study, ensuring that participants were residents of communities sampled. Villages with a population exceeding 2000 were excluded as larger, urban areas tend to have a more transient population, and it would have therefore have been difficult to follow residents of the November 2014 census up. In the absence of prior similar studies, a conservative pre‐study sample size was calculated utilizing Raosoft (Vovici, Seattle, Washington, USA) assuming a 50% prevalence of infection and population size of 20 000. 754 children were required to detect the prevalence of LRTI with 5% precision at the 95% confidence level. A list of the 72 HSAs in Monkey Bay was obtained. Five HSAs were excluded for having communities with a trading post. 17 HSAs were excluded for overseeing an estimated population exceeding 2000, leaving 50 HSAs eligible for selection. Six HSAs were selected using a random number generator from an alphabetical list. These oversaw eight villages. Within villages, all children aged 0‐59 months were sampled. Households were notified in advance of the researchers’ attendance and the purpose of the study by HSAs. Children were brought to a central location by their parent, and residence in the village was confirmed. After all children had been seen, households in the community were visited door‐to‐door, enabling all resident children to participate. Villages were visited on at least two separate occasions to ensure that children absent on the first visit were sampled. The purpose and procedures of the study were explained to local health authorities and permission obtained from village chiefs, aided by a trained translator. Following parental consent to participate, children were allocated a unique identification number under which data were entered. A verbal survey, obtained from participants’ parents and facilitated by a translator, elicited data on risk factors including maternal educational level (as a proxy for socio‐economic status), clustering of disease (another child with ARI recorded in their health passport in the last 12 months in the household) and number of rooms in household and number of household residents (household density). To determine the annual prevalence of ARI, health passports were examined. These are patient‐held records of all consultations with healthcare professionals. A positive diagnosis of ARI was recorded if an acute respiratory tract infection with clinical signs of pneumonia treated with antibiotics, lower respiratory tract Infection, or pneumonia was documented in the passport in the 12 months prior to the date of visit or since birth in infants less than a year old. Children’s vaccination records, contained within the passport, were also inspected. Whether children had received all age‐appropriate PCV vaccinations and EPI mandated vaccinations for their age (as a proxy for access to health care) were recorded. In older health passports, before the addition of PCV to EPI, data on PCV status were not included in analysis as it was not possible to definitively ascertain whether or not they had received vaccination. Assenting children were then examined physically to determine the point prevalence of ARI using integrated management of childhood illness (IMCI) guidelines by doctors/medical students from the United Kingdom who had been trained in assessing children using IMCI.27 Parents were asked whether their child currently had a cough and about the presence of IMCI general danger signs. The child’s temperature was taken. Children’s chests were then exposed and evidence of increased work of breathing (indrawing or subcostal recessions) observed. Next, respiratory rate was counted for one minute during which time the researcher listened for stridor. A positive clinical diagnosis of ARI was recorded if a child had a cough and tachypnoea (respiratory rate >50/minute in children <12 months old, respiratory rate >40/minute in children >12 months old) or cough and chest indrawing or stridor when calm. Finally, children were assessed for malnutrition following Integrated Management of Childhood Illness Guidelines.27 Participants with pitting oedema present for more than two‐seconds after the researcher pressed their thumb inferior to the medial malleolus for three‐seconds were classified as acutely malnourished. Weight was measured to the nearest 0.02 Kg, with shoes and outer clothes removed, using scales that were calibrated each day. Participants aged 0‐23 months had length measured to the nearest 0.1 cm using a length board. Participants aged 24‐59 months had height measured to the nearest 0.1 cm using a vertical Leicester Height Measure®. All measurements were taken three times, with the median measure used. Measurements were then plotted on Weight‐for‐Height (acute malnutrition), Height‐for‐Age (chronic malnutrition) and Weight‐for‐Age (acute‐on‐chronic malnutrition) z‐score growth charts. Measurements plotted below ‐2 standard deviations from normal were classed as malnourished.27 Data were entered into Microsoft Excel (Microsoft, Redmond, Washington, USA) on a tablet device at the time of gathering. Data were then checked, coded and entered into spss version 22 (IBM, New York, USA) for analysis. Demographic data were first analysed. Continuous variables were tested for normality. Mean and standard deviations (S.D.) were calculated for normally distributed variables. Median and interquartile ranges (IQR) were analysed for nonparametric variables. The percentage of participants with each categorical variable was calculated. The annual prevalence of ARI was the percentage of children with one or more episodes of ARI recorded in their health passport. The point prevalence of ARI was the percentage of children classified with clinical ARI following physical examination. For all prevalence data, 95% confidence intervals (CI) were calculated. Univariate analysis determined potential predictor variables for current and annual ARI. Chi‐square tests examined the significance of differences between groups. Mann‐Whitney U tests examined the association between age and ARI. Variables demonstrating significance at the P < 0.10 level were entered into binary logistic regression models, for annual prevalence of ARI and point prevalence of ARI, to identify independent risk factors. Ethical approval for this study was obtained from University of Birmingham BMedSci Population Sciences and Humanities Internal Ethics Review Committee (reference no. 2014‐15/CI/LJ/04), London School of Hygiene and Tropical Medicine (reference no. 6500) and Malawi College of Medicine Research Ethics Committee (reference no. P.02/14/1521).