Factors associated with increased risk of progression to respiratory syncytial virus-associated pneumonia in young Kenyan children

Objectives: To identify factors associated with developing severe respiratory syncytial virus (RSV) pneumonia and their commonality with all-cause lower respiratory tract infection (LRTI), in order to isolate those risk factors specifically associated with RSV-LRTI and identify targets for control. Methods: A birth cohort of rural Kenyan children was intensively monitored for acute respiratory infection (ARI) over three RSV epidemics. RSV was diagnosed by immunofluorescence of nasal washings collected at each ARI episode. Cox regression was used to determine the relative risk of disease for a range of co-factors. Results: A total of 469 children provided 937 years of follow-up, and experienced 857 all-cause LRTI, 362 RSV-ARI and 92 RSV-LRTI episodes. Factors associated with RSV-LRTI, but not RSV-ARI, were severe stunting (z-score ≤-2, RR 1.7 95%CI 1.1-2.8), crowding (increased number of children, RR 2.6, 1.0-6.5) and number of siblings under 6 years (RR 2.0, 1.2-3.4). Moderate and severe stunting (z-score ≤-1), crowding and a sibling aged over 5 years sleeping in the same room as the index child were associated with increased risk of all-cause LRTI, whereas higher educational level of the primary caretaker was associated with protection. Conclusion: We identify factors related to host nutritional status (stunting) and contact intensity (crowding, siblings) which are distinguishable in their association with RSV severe disease in infant and young child. These factors are broadly in common with those associated with all-cause LRTI. The results support targeted strategies for prevention. © 2008 Blackwell Publishing Ltd. The study was conducted in Kilifi, a rural district on the coast of Kenya with a tropical climate and seasonal rains (March–July and October–December). The community is served by a district hospital (KDH) based in Kilifi town. Ethical permission was provided by the Kenya National Ethical Review Committee and Coventry Research Ethics Committee, UK. The terminology used for respiratory disease throughout the text is described in Table 1. Terminology used for disease types Full details of the birth cohort study have been described previously (Nokes et al. 2004, 2008; Okiro 2007). Briefly study participants were recruited between January 2002 and May 2003, from KDH maternity ward and the maternal child health clinic (if <2 weeks old), and if their homes were within easy access to the hospital. Written informed consent was obtained for participation. Surveillance continued until each child had experienced three RSV epidemics. These epidemics were clearly defined, occurring on an approximately annual basis, and lasting for between 14 and 21 weeks (mean 17 weeks) (Nokes et al. 2008). Households were visited by trained study field workers (FW) weekly during, and monthly outside of RSV epidemics. Potential cases of LRTI identified by a FW during home visits were referred to the clinic, and given one way bus fares. These referral cases were recognized by cough or difficulty in breathing (on the day or a history over the preceding week) in association with fast breathing for age (50 or more breaths per minute in infants, and 40 or more breaths per minute otherwise), or (alone or accompanied by) the presence of lower chest wall indrawing (World Health Organization 2005) or difficulty in breathing alone if observed on the day of the visit. ARI surveillance through presentation at the research out-patient (OP) clinic at KDH was maintained throughout the follow-up period either by self (passive) referral, or FW (active) referral at home visits. To enhance passive surveillance (self referral), mothers were encouraged to bring their child to the research clinic if they identified any symptoms of respiratory infection. At the OP clinic, the severity of respiratory disease was ascribed following a review by a study clinician, which would include (a repeat) measurement of respiratory rate. Transport costs were reimbursed, and definitive medicines were provided without charge. At each contact with study participants identification of symptoms consistent with ARI on the day or during the preceding week, and an absence of RSV infection for the prior 14 days, prompted the collection of a nasal specimen by nasal washing. Specimens were examined for RSV antigen by direct immunofluorescence test (DFA, Chemicon). The severity of respiratory disease was ascribed following a clinical review using a standard proforma and based on WHO guidelines (Nokes et al. 2004; WHO 2005). Between June and November 2004 a cross-sectional risk factor survey was carried out on households of all birth-cohort children remaining under surveillance. The purpose of the study was explained to the parents or guardians and verbal consent sought before the interview commenced. A household was defined as all individuals who normally eat at the same meal. Individuals 15 years of age or older were considered adults. The questionnaire was based on previous risk-factor surveys conducted in sub-Saharan Africa (Ballard & Neumann 1995; Weber et al. 1999; Broor et al. 2001) addressing household characteristics, and demographic, socioeconomic and environmental factors, but tailored to the specific setting of the study community. Data related to key asset indicators including primary caretaker (PCT) education level, occupation of the major income provider (MIP), housing characteristics (type of walls, sanitation), source of drinking water, family size and sleeping patterns in relation to the birth cohort child and nutritional status was collected. Crowding and contact intensity was measured by the total household size, number of sibling children in the household, and sleeping proximity. A wealth index was constructed from data on household asset ownership (e.g. owning a bicycle) and characteristics (e.g. house and toilet type) using principal component analysis (Filmer & Pritchett 2001). Weights (scoring coefficients) derived from the first principal component were used to assign each household a wealth index from which socioeconomic groups were defined as follows: the top 33% were referred to as ‘least poor’, the next 33% as ‘poor’ and the bottom 34% as ‘most poor’. Anthropometric measurements were obtained at birth and at 3-month intervals thereafter for cohort children. A WHO macro [igrowup_STATA macro (WHO 2006b) ] was used to calculate z-scores (the standardized deviation from the median of a reference population) for three anthropometric indicators: weight-for-age (waz-underweight), length or height-for-age (haz-stunting), weight-for-length or height (whz-wasting). Data were double entered onto FileMaker (FileMaker Pro 5.5 v1) with internal consistency checks, and analysed using Stata (v8.2, STATACorp, Texas). Longitudinal data on infection history were combined with cross-sectional data from the risk factor survey. Observation time included days from date of recruitment until the last study visit, or until lost to follow-up, excluding days absent from the district. Each child had multiple record visit data over the follow-up period. Certain variables were reassigned at intervals of 3 months (nutritional status) or at each epidemic period (number of siblings sleeping in house, rooms and beds). For the purpose of analysis only clinical data obtained from CO reviews were used (as opposed to that of the FW) and a diagnosis of LRTI was assigned to children with acute cough or difficulty in breathing in association with any one or more of the following (i) raised respiratory rate for age (respiratory rate of ≥40 breaths/min for children aged >12 months, ≥50 breaths/min for ages greater than 1 month, and ≥60 for a child of any age), (ii) lower chest wall indrawing or (iii) inability to feed, reduced conscious level or hypoxia (O2 saturation <90% by Oximetry), the latter group only if confirmed by the clinician’s own diagnosis of LRTI or bronchiolitis. The outcome variables were: (i) all-cause LRTI, (ii) RSV-ARI and (iii) RSV-LRTI (as defined in Table 1). Univariate analysis was performed to describe the study population and identify risk factors for inclusion in multivariate analysis. Predictors were considered for inclusion in the multiple regression models using the log-rank test of equality of survival distribution across strata (for categorical variables) or a univariate Cox proportional hazard regression for the continuous variables. Predictors were considered for inclusion if the test had a P-value of 0.25 or less, and for groups of collinear variables (e.g. household contact measures) only those with the strongest univariate association were included. Significant variables were included in the multivariate models using a non-automated forward stepwise regression starting from the variable with the highest test statistic. Variables that no longer showed significance (P ≥ 0.05) were removed. For highly correlated variables (r ≥ 0.8) only the variable remaining significant in the multivariate model was included. The Cox shared frailty model was used with the all-cause LRTI outcome because of significant multiple failures per individual (θ = 0.326, P < 0.001). The standard Cox model with adjusted standard errors adjusting for clustering within individual was used for RSV-ARI and RSV-LRTI. Analysis time was calendar time, eliminating the potential confounding effect of seasonality in RSV and all-cause LRTI. Time-varying covariate(s) were specified through multiple observations per subject, ensuring risk sets at each failure were associated with the correct value of the risk factor. The results are reported as relative risks (hazard ratios) with 95% confidence intervals.