In the Xhosa townships surrounding Cape Town, 37 neighborhoods of about 500 households each were identified to participate in the project. The neighborhoods contain a variety of housing, including formal settlements (government housing with onsite water and sewage connections), site-and-service plots (plots of land where residents can build a home, with some access to water and sanitation facilities) and informal settlements (shacks or temporary structures that rarely have water on the premises and are not on a specified plot of land). For each neighborhood, a Mentor Mother (MM) was screened, recruited and trained. Recruitment and training of MMs is described below.
MMs canvassed their neighborhoods, entering each household and inquiring if there were any children under six years of age living in the home. When children were present, the MM weighed each child and plotted the weight on a growth chart that was shown and explained to the parent(s). If the MM identified a child whose weight indicated malnourishment, the household was eligible to participate in the study. Malnourishment was defined as having a weight more than two standard deviations below the World Health Organization (WHO) normative mean weight for the child's age. Children in this range are in the bottom 2% in weight for age.
From November 2002 to July 2004, the 37 MMs recruited 684 mothers with malnourished children under the age of six years; if there was more than one malnourished child, only one was selected to be followed for this study. The mother–child unit in each household is referred to as a dyad. Dyads recruited into the study were scheduled for a baseline assessment, after which they were randomized to either the intervention or control arm of the study. displays the flow of participants through the study. Assignment to the treatment condition was based on a random sequence decided a priori for every three households enrolled into the study. MMs were provided with randomly sequenced numbered folders containing the randomization assignments. Once a dyad was enrolled the MM selected the next folder in her possession, and assigned the dyad accordingly. Two out of each three households were assigned to the Philani intervention condition (n = 500). The third household became a control case (n = 184). Five dyads were assigned initially to the control condition but were removed from the analysis and were provided services for ethical reasons because the child's life was endangered; the final sample size in the control condition was thus n = 179.
Outline of flow of participants in the study.
During the year following recruitment, MMs provided the intervention home visits with growth monitoring to those dyads randomized to receive it. Dyads in the control arm of the study did not receive these visits. In addition, MMs conducted follow-ups with control dyads approximately every six months, at which time they weighed the children. After their final weighing, dyads in the control condition were given the option to receive the Philani nutrition intervention program. The follow-up period ended in September 2005. The study was approved by the Institutional Review Board at UCLA and was registered with ClinicalTrials.gov (NCT00995592).
Mentor Mothers were nominated initially by local community leaders or by open application. Criteria included having thriving babies, demonstrating good communication and strong interpersonal skills, being committed to community service and showing a disciplined personal and professional lifestyle. The nominees were interviewed and trained by the Philani outreach supervisors and received home visits to observe routines and confirm that the households met the criterion of “thriving” (i.e. the home was organized, children were monitored, healthy food was available). Only about 50% of potential MMs remained after this process; these MMs were engaged to recruit participants and deliver the home-based interventions. They received a stipend of $US 130/month and were expected to work for four hours per day.
Mentor Mothers received four phases of training: (1) watching experienced MMs implement the intervention in an inspiring manner; (2) attending training sessions covering nutrition, basic child health, weighing babies and completion of growth charts, how to recognize danger signs and crisis situations and how to encourage depressed mothers to be more active and engaged with their children; (3) learning how to build trust with mothers and use the relationship to improve the consistency of healthy daily routines; and (4) implementing the first round of home visits independently in their neighborhoods. The intervention supervisor visited at least one day per month on a random schedule to ensure that the implementation was proceeding as planned. The supervisor collaborated with the MM in problem-solving and generating action plans when problems occurred in the field. The quality of implementation was monitored by reviewing the forms completed at each home visit, monitoring visitation patterns, collecting observations by outreach supervisors and brief ratings of home visits by the outreach supervisors.
The frequency of MM visits was based upon need. For example, if there was a very small low-birth weight baby, the family might be visited two to three times a week for a week or two until the MM was confident that the child's mother was coping well. If a child was improving and gaining weight that dyad could be visited every two–three weeks. When the child was almost fully rehabilitated visits might occur once a month. Typical MM home visits lasted from 20 minutes to one hour. During the visits, the MM weighed the child and discussed developmental progress with the mother. The MM also ensured that the mother had applied for appropriate social grants and understood proper nutrition and hygiene. MMs stressed the importance of breastfeeding, the proper time to introduce solid food, frequent feeding and a mixed diet that includes fruits and vegetables. The MMs checked that immunizations were up to date and that the child had been dewormed. Among the families in each MM's caseload there was likely to be one emergency per week; for example, a child with a high fever, difficulty breathing or appearance of severe dehydration. These cases were brought to the Philani health clinic or the local public health clinic to receive immediate attention. As part of the intervention program, MMs established neighborhood meetings where mothers gathered to discuss child health and nutrition issues.
The following measures were assessed:
• Maternal and household characteristics. At recruitment, mothers reported their age, number of years they had been in Cape Town, number of living children, marital status and housing conditions (classified as formal, site and service or informal). Interviewers reported two subjective assessments of the mothers’ living conditions: overall smell (classified as pleasant, neutral or poor) and hygiene (classified as good, average or poor).
• Children's characteristics. At recruitment, mothers reported on several characteristics of the child enrolled in the study, including: age, gender, birth weight, whether the child's meals had been reduced in size or skipped in the past year due to lack of money and whether or not the child was already enrolled in a nutrition program. At recruitment and follow-ups, child weight was measured in kilograms. In addition, a weight-for-age Z-score (WAZ) was calculated and standardized according to reference weights from the Centers for Disease Control and Prevention growth charts (Kuczmarski, Ogden, & Grummer-Strawn, 2000).
We compared demographic and household characteristics of the dyads across intervention conditions at recruitment. We also compared dyads followed over time versus those lost to follow-up; χ2 tests and t-tests were conducted for categorical and continuous measures, respectively. Where appropriate, Fisher's exact test was conducted on categorical measures with sparse cell counts and the Wilcoxon two-sample test was conducted on continuous measures with skewed distributions.
Mixed-effect linear regression models were fitted in SAS software version 9.1 (SAS Institute Inc., Cary, NC, USA) using the PROC MIXED procedure to evaluate the impact of the intervention on the child's weight (in kilograms and weight-for-age Z-score) over the year following recruitment. Random intercepts were included for each MM and each child to account for the hierarchical structure of the data. We also modeled an autoregressive (AR) covariance structure to account for variability between repeated evaluations not accounted for by the random intercepts. The longitudinal model estimates separate baseline means and trajectories for each intervention condition. In doing so, the model allows baseline and trajectory differences across intervention conditions to be disentangled and estimated separately.
Models included covariates for relevant background characteristics (i.e. characteristics anticipated to be associated with child weight or found to differ across intervention conditions); an intervention condition indicator to control for baseline differences in child weight across intervention conditions; time from recruitment; and a time × intervention condition two-way interaction to model both separate mean weights at recruitment and weight trajectories over time for the intervention and control conditions. Based upon the curved trajectories found in infant growth charts, we anticipated that weight would change in a non-linear manner over the course of the year. Therefore, we also tested covariates for a quadratic time trend to model non-linear weight changes in the overall sample and a three-way interaction between quadratic time and intervention condition to model additional non-linear weight changes in the intervention condition; quadratic covariates were retained if significant. The model for weight in kilograms also included age of the child at recruitment as a covariate; weight-for-age incorporates age into the outcome measure.