Family networks and infant health promotion: A mixed-methods evaluation from a cluster randomised controlled trial in rural Malawi

Objective Parents may rely on information provided by extended family members when making decisions concerning the health of their children. We evaluate whether extended family members affected the success of an information intervention promoting infant health. Methods This is a secondary, sequential mixed-methods study based on a cluster randomised controlled trial of a peer-led home-education intervention conducted in Mchinji District, Malawi. We used linear multivariate regression to test whether the intervention impact on child height-for-age z-scores (HAZ) was influenced by extended family members. 12 of 24 clusters were assigned to the intervention, in which all pregnant women and new mothers were eligible to receive 5 home visits from a trained peer counsellor to discuss infant care and nutrition. We conducted focus group discussions with mothers, grandmothers and peer counsellors, and key-informant interviews with husbands, chiefs and community health workers to better understand the roles of extended family members in infant feeding. Results Exposure to the intervention increased child HAZ scores by 0.296 SD (95% CI 0.116 to 0.484). However, this effect is smaller in the presence of paternal grandmothers. Compared with an effect size of 0.441 to 0.467 SD (95% CI â -0.344 to 1.050) if neither grandmother is alive, the effect size was 0.235 (95% CI â -0.493 to 0.039) to 0.253 (95% CI â -0.529 to 0.029) SD lower if the paternal grandmother was alive. There was no evidence of an effect of parents’ siblings. Maternal grandmothers did not affect intervention impact, but were associated with a lower HAZ score in the control group. Qualitative analysis suggested that grandmothers, who act as secondary caregivers and provide resources for infants, were slower to dismiss traditionally held practices and adopt intervention messages. Conclusion The results indicate that the intervention impacts are diminished by paternal grandmothers. Intervention success could be increased by integrating senior women. This is a secondary, sequential mixed-methods study based on a cluster RCT of a peer-led home-education intervention conducted in Mchinji District, Malawi. We investigated family member roles in the success of the intervention, which provided information on healthy infant feeding practices, with quantitative data collected between November 2008 and January 2010, and qualitative data collected in December 2015. Full details of the original trial and methods have previously been published.30 31 The quantitative data were collected and analysed first, and used to design the qualitative aspect of the study. The overall interpretation of our findings was integrated following analysis of the qualitative data. Mchinji is a rural district in central Malawi with a population of about 455 000.32 Maternal and infant healthcare is delivered at one district hospital, four rural hospitals, nine health centres, private clinics and in the community through government employed community health workers (CHW—known locally as Health Surveillance Assistants). Much of the healthcare received by pregnant women and infants is in the community setting by CHWs, or at home by kin and other social contacts. However, Malawi has medical pluralism, with traditional practices, beliefs and behaviours such as witchcraft and herbal medicine being commonly used alongside Western medicine. The 2010 Malawi Demographic and Health Survey reported 24% of births in the region occurred in the woman’s own home and 2% in someone else’s home, and many births are not attended by medically trained healthcare personnel but by traditional birth attendants (14.4%), friends and relatives (8.7%) or no one (2.6%).16 Without access to a skilled birth attendant, women are more vulnerable to infection and complications during birth; the infant mortality rate in 2010 was of 66 per 1000 live births.16 Traditionally, the main ethnic group in the study area, the Chewa, are a matrilineal and matrilocal group. Matriliny is a system in which land is passed through the female line. Under traditional matrilocal norms, husbands move to their wives’ homes after marriage unless they make a special payment. However, following the influence of patrilineal and patrilocal ethnic groups and British colonialists, there is evidence that matrilocality has waned over time, but not completely.33 34 As a result, women often remain in close proximity to their own relatives after marriage. For the RCT, Mchinji was divided into 48 approximately equal population clusters based on the 1998 Malawi Population and Housing census (the most recent census at the time of trial planning). Within each cluster of around 8000 people, the 3000 individuals living in villages closest to the geographical centre were enumerated as the eligible study population. Twelve clusters were assigned to the infant feeding intervention only and 12 served as controls. Full details of the trial set-up and methods are described by Lewycka et al.30 All women living in clusters assigned to the infant feeding intervention who became pregnant during the trial period were eligible to receive five home visits from a trained local woman volunteer (‘peer counsellor’) to discuss maternal and infant healthcare issues; around 60% of eligible women reported having been visited. The visits were timed to coincide with key stages of infant development (the third trimester, and at 1 week, 1 month, 3 and 5 months after birth). Each visit focused on a specific set of topics for discussion, with special attention paid to nutrition practices including exclusive breast feeding, and complementary feeding. Peer counsellors were literate local women aged 23–50 years with breastfeeding experience, who each covered a population of about 1000 people. The intervention began in December 2004, with an initial establishment period until June 2005. The trial was ongoing at the time of the quantitative data collection. Following the end of the trial period, peer counsellors continued to receive mentorship and supervision support from government CHWs and the local implementing non-governmental organisation (NGO). In 2015, at the time of qualitative data collection, approximately one-third of the volunteer counsellors were still active in delivering the intervention. A baseline census was conducted in all clusters in 2004, prior to the start of the intervention. All women aged between 10 and 49 years were enumerated and a random sample of 104 women aged between 17 and 43 years per cluster was then drawn to be interviewed for two follow-up quantitative surveys as part of this secondary study. Sampled women (‘main respondent’ hereon) were visited to complete the first follow-up in November 2008 to March 2009, and a second follow-up in October 2009 to January 2010. Each follow-up survey contained questions about the size of the extended family of the main respondent and her husband (those alive and those in the village), the health of all household members, food and liquid intake of children aged under 6 years, knowledge about child nutrition, intervention participation (in treatment clusters) and socioeconomic variables such as adult work. The height of the main respondent and the height and weight of children under 6 years were also collected by trained enumerators. The main outcome for our analysis is the child HAZ score, which is a long-term indicator of health that reflects nutrition and morbidity since birth, and should be sensitive to any effects of intervention exposure in early life. It is calculated by comparing the height of the child with the median height in the WHO reference population of children of the same gender and age in months.35 The sample was balanced between treatment and control clusters along a range of variables collected at baseline17 (table 1). The baseline characteristics of the two groups remained similar even after accounting for attrition between the baseline and first endline survey, indicating that randomisation was not jeopardised (table 1). Distribution of household and women characteristics in controls and differences with treatment group Household and mother level characteristics in 2004 corresponding to married main respondent mothers present in the second follow-up survey with children born after the intervention began in July 2005. *p<0.1, **p<0.05, ***p<0.01. P values are calculated using the wild cluster bootstrap t procedure described by Cameron et al.37 †Continuous variable, for which the mean is reported. ‡ Binary variable, for which proportions are reported. For this analysis, we use a sample of children who were born since July 2005; and whose mothers are married main respondents in the follow-up surveys (80% of the sample). This sample selection ensures that we measure effects on children whose mothers were eligible to receive visits from a peer counsellor; and allows us to compare effects of the mothers’ relatives with those of her husband. Children in the estimation sample were aged between 0 and 53 months at the time of the endline surveys. Online supplementary appendix 1 provides a timeline of the original trial and the quantitative data collection, and of our sample inclusion criteria. bmjopen-2017-019380supp001.pdf Table 1 presents the means of basic demographic and socioeconomic characteristics for women in the analysis sample living in control clusters at baseline, the differences in the means between the control and treatment groups and the p value of this difference. The last two columns allow us to assess whether the randomisation holds in our selected sample. Women assigned to the control group were 24.6 years on average; 71.8% were married and while 70.1% had completed at least primary education, only 7.6% had completed secondary education. In line with the general profile of communities in Mchinji, 95.4% of sampled women were Chewa ethnicity and 98.3% were Christian. The average household size was 5.6 members and all households were engaged in agricultural activity. Table 2 displays statistics on the size of extended family networks of the children in our analysis sample. Most children have their grandmothers alive (87.3% have maternal grandmothers alive and 80.7% have paternal grandmothers) and their parents have a relatively large number of siblings, with an average of more than two brothers and two sisters each. Distribution of family networks indicators in controls and differences with treatment group for sampled children. Sample includes all children born since July 2005, who were aged 0–53 months at the time of interview, and whose mothers were married main respondents to the follow-up surveys in 2008–2009 and 2009–2010. A pooled dataset from both follow-up surveys is used to construct means. *Binary variable for which percentages are reported. The quantitative analysis aims to determine how different family members influence the effectiveness of the infant feeding intervention. Before estimating the main model, we study the relationship between baseline characteristics of mothers and their households and measures of the extended family using linear regression. Table 3 reports these results. It indicates that children whose grandmothers are alive have on average younger mothers, who are more likely to have completed at least primary education, less likely to be working as farmers in 2004 and are from more socioeconomically advantaged households, as measured by a composite wealth index constructed using principal components analysis as recommended by Filmer and Pritchett.36 Relationship between baseline characteristics and family network size, with p values Ordinary Least Squares regressions with baseline characteristics gathered in 2004 as the dependent variable and family networks as independent variables. Sample contains married main respondent mothers present in the second follow-up survey with children born after the intervention began in July 2005. SEs computed using the cluster-correlated Huber-White estimator are reported in parentheses and p values are also reported in parentheses. P values are calculated using the wild cluster bootstrap t procedure described by Cameron et al. 37 The wealth index was calculated using principal components analysis as recommended by Filmer and Pritchett.36 *p<0.10, **p<0.05, ***p<0.01. Our main specification is the following linear multivariate regression: where HAZij is the height-for-age z-score of child i in cluster j. Tj is a treatment exposure indicator, which captures whether the child was born to a mother living in 2004 (pre-intervention) in a cluster that was assigned to receive the programme. We therefore use an intent-to-treat estimator. Maternal_grandmotherij and Paternal_grandmotherij are binary variables indicating, respectively, whether the maternal and paternal grandmother is alive. Total_mothers_siblingsij (Total_fathers_siblingsij) captures the total number of siblings of the child’s mother (father) who are alive. We use two definitions of this variable in different specifications of the model: (i) brothers and sisters (separately) of each parent and (ii) the total siblings of each parent. Xij and Zj are vectors of control variables at the individual and cluster level, respectively. These include all baseline characteristics where significant differences between households with different extended family members alive were detected, and interview month and year indicators to account for month-year-specific shocks. We do not adjust the data for missing information. We fitted three models, one crude model with the intervention term only, and two full models as specified in the equation each treating parent siblings differently. The coefficient β captures the effect of the programme for children whose maternal and paternal grandmothers are dead, and whose parents are only children, while the coefficients β2, β4, β6 and β8, represent the effects of the extended family members on HAZ scores in the control group. The coefficients β3, β5, β7 and β9, associated with interaction terms between variables capturing extended family relations and the indicator for programme allocation, estimate the additional effect of the programme for children with different types and numbers of extended family members. A positive (or negative) significant interaction provides evidence that the programme effect is enhanced (or diminished) in the presence of that particular family member. Errors εij are assumed to be uncorrelated between individuals in different clusters but are allowed an unrestricted correlation structure within clusters. To account for correlation within clusters, SEs must be adjusted to prevent downward bias, and incorrect inference. Given the small number of clusters in the study (12 intervention and 12 control clusters), we adopt wild cluster bootstrap methods as recommended by Cameron et al.37 Associated 95% CIs can be calculated using a computationally intensive method suggested by Colin Cameron and Miller.38 The bootstrap adjustment applied here was studied in detail by Fitzsimons et al and was found to perform well.17 Data from both follow-up surveys are pooled to improve statistical power. The extended family network is defined according to which members of the family are alive, rather than which ones live in the same village or household. This is in case treatment exposure affected decisions over where to live, which would cause a measure of family network size based on residence to be correlated with the intervention and thereby bias estimates. The benefit of defining the size of the family network according to which members are alive is that this is almost certain to be invariant to programme exposure. We choose to define Tj by exposure to the intervention rather than actual participation since participation in the programme was voluntary and also relied on the ability of peer counsellors to locate eligible women. Women who peer counsellors did not manage to trace or who chose not to take part in the programme may be different from those who did participate. The existence of such systematic differences would potentially introduce some unobserved correlation between the treatment interaction variables and HAZ scores if Tj were defined on the basis of actual participation. Indeed, Fitzsimons et al report that women who received the visits tend to be poorer.17 Defining treatment based on residence at baseline rather than at the time of the follow-up interviews also alleviates concerns of bias in case there was purposeful migration into treated areas by control-group assigned households. Following the findings from the quantitative analysis, we conducted focus group discussions (FGDs) with grandmothers, mothers and peer counsellors, and semi-structured interviews with fathers, CHWs and village chiefs to gain a more in-depth understanding of family roles and how grandmothers might influence child health. Participants were recruited from 11 of 24 intervention and control clusters across the district in late 2015. Mothers, grandmothers and fathers were purposively selected by CHWs and chiefs to represent those households who had actively received the intervention or had children aged under 5 years in control clusters. Volunteer peer counsellors were contacted directly, to represent a range of ages and years’ experience as counsellors. Chiefs and CHWs were purposively selected and contacted directly to represent clusters with a range of engagement with the intervention. We planned to conduct a total of 5 FGDs and 10 interviews, rather than collecting data until saturation was reached. FGDs and interviews used topic guides, based on the quantitative findings and wider literature on infant feeding behaviours, covering: household decision making around feeding, infant feeding practices, feeding knowledge and sources of information about infant feeding. We asked about all household members, and specifically probed about the role of grandmothers. All discussions were facilitated by two local trained qualitative researchers in Chichewa. Participants were reimbursed for their travel expenses and given refreshments. All discussions were audio recorded, and then verbatim transcribed in Chichewa. Transcripts were translated into English as a group, with ambiguous terms or phrases debated until a consensus meaning was reached. Data collection, transcription and translation were conducted by EK, HC, TP and FB—female Malawian researchers who are fluent in English. The English transcripts were coded using an inductive framework approach based on the following steps: familiarisation, coding, developing and applying the framework, charting and interpretation.39 All transcripts were double-coded, as a group by TP, EK, HC and FB and independently by CK—a female British researcher with 5 years’ work experience in Malawi. Coding was done on paper and the coding matrix developed in Microsoft Excel. A round-table discussion was then conducted by all five researchers to compare the codes and agree on themes; disagreements in coding were discussed until an agreement on the interpretation was reached. The original trial was conducted with extensive community engagement, including initial planning and dissemination meetings with village, healthcare and local government committees. These groups were involved in the recruitment of participants for interviews and focus group discussions. The quantitative survey instruments were pretested on households living in buffer areas. All participants gave informed written consent.