Maternal/Child Social Support and Food Security in Relation to Child Height and Bmi in Four Low- and Middle- Income Countries: Mediation Analysis of Young Lives Data

32 Background 33 Poor nutritional status in childhood is associated with an elevated risk of mortality and morbidity 34 later in life. Previous studies showed a positive association between specific types of social capital 35 and child nutritional status. Our study examined whether improved food security mediates the 36 impact of maternal and child social support on child height and body mass index (BMI) in four 37 low- and middle-income countries. We used data from the Young Lives cohort study comprising roughly 1,000 children at age 8 and and Peru. Outcome variables were z-score for BMI Strengthening social support to improve child nutritional status may not be a sufficient 52 intervention in resource-poor settings because sources of supports may lack sufficient food 53 resources to share. Considering between-country heterogeneity, a “one size fits all” approach for 54 enhancing social capital may not be appropriate. 55


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Poor nutritional status in childhood has been linked to elevated risk of mortality and 72 morbidity later in life. 1 Not only does impaired physical growth hamper child development 73 (defined as the attainment of gross motor and fine motor skills), psychosocial competencies, and 74 cognitive abilities, 2 3 it also raises a risk of infectious disease. 4 However, the worldwide prevalence 75 of child anthropometric failure including stunting, underweight, and wasting remain stubbornly 76 high and are concentrated in Low and Middle-Income Countries (LMICs). In 2019, 38% and 34.5% 77 of children aged 0-59 months in Eastern Africa and Oceania were estimated to have stunting 78 respectively, which is more than 15 times higher than in Northern America (2.6%). 5 79 According to the United Nations Children's Fund (UNICEF) framework of determinants 80 of child undernutrition, household food security is one of the important factors for child 81 undernutrition which is in turn affected by socioeconomic conditions and the national/global 82 context. 6 Food insecurity leads to inadequate dietary intake which affects height and weight 83 directly as well as indirectly by promoting disease occurrence. This was empirically demonstrated 84 in Humphries (2015) where children from chronically food-insecure households in Ethiopia, India, 85 Peru, and Vietnam had significantly lower Height for Age Z-score (HAZ) compared to 86 households that were consistently food-secure. 7 87 Social capital, defined as the resources embedded within social networks, 8 has been 88 demonstrated to positively affect health. Social capital can be analyzed as an individual attribute, 89 i.e., as an individual's access to social support within a network. Social capital can be analyzed 90 also as a property of the collective, e.g., norms of mutual assistance within a group. 9 10 Although 91 social capital has long been discussed in social sciences, the emergence of social capital in 92 development practice is relatively recent. 11 Several studies have found a positive association 93 between maternal or household social capital and child nutritional status. 12-15 However, it is 94 difficult to reach any definite conclusion because characteristics of the sample and measure of 95 social capital varied from study to study, and the results have been mixed. 12-15 96 Studies that found a positive association between social capital and child nutritional status 97 suggested that increased food security may be the mechanism, whereby individuals share food 98 resources within their network or gain access to knowledge of where to obtain cheap sources of 99 food. A handful of studies have demonstrated an association between social capital and 100 household hunger or food security. [16][17][18] However, most of these took place in high-income 101 countries (HICs) where food security is good on average, and therefore, there is an abundant 102 source of supports that food-insecure households can borrow food or receive food assistance from. 103 Only one study based in the LMIC setting has examined the role of social capital in the context of 104 a food support program within their community. 19 Furthermore, none of studies examined the 105 mediating role of food security in the effect of social capital on child nutritional status in any 106

settings. 107
The results from these prior studies about association among maternal social capital, food 108 security, and child nutritional status calls for the need to assess the role of food security in the 109 association between social capital and child nutritional status in LMICs. Although school-age 110 children are old enough to develop their own social networks or to participate in groups while 111 they are still in a growing phase, no studies have evaluated the association between child's social 112 support and their nutritional status. Thus, our study aimed to examine 1) whether maternal and 113 child social support is associated with child height and Body Mass Index (BMI) 2) whether these 114 associations are mediated by food security. The YL study employed a clustered multistage sampling strategy in each country. At the 125 first stage, 20 sentinel sites were selected in each country by semi-purposive sampling with slight 126 oversampling of poor sites to serve the main study objective to explore the causes and 127 consequences of childhood poverty. 20 For example, the most food-insecure areas encompassed the 128 sampling universe in Ethiopia. In Peru, the richest 5% of districts were excluded from the sample. 129 However, final samples represent a range of regions, policy contexts, and living conditions. 7 The 130 cohort in India consisted only of households from Andhra Pradesh while cohorts in the other 131 three countries were nationwide. At the second stage, all households with children of the right 132 age within the sites were listed, from which 100 households were randomly selected at each site. 21 133 The response rate was above 90% in all the countries. Data were collected by a standardized, 134 interviewer-administered questionnaire from the child's main caregiver. 135

Ethical review 136
Approval for this study was granted by the Social Science Division of Oxford University, and 137 research ethics committees in Ethiopia, India, Vietnam, and Peru. 138

Child anthropometry 140
We assessed both child height and BMI, which is affected by chronic and acute nutritional 141 status respectively. 22 Height was measured using stadiometers with standing plates and moveable 142 headboard which were locally made, and weight was measured by calibrated digital balance 143 (Soehnle). Height-for-Age Z score (HAZ) and BMI for -Age Z score (BAZ) were calculated using 144 the WHO 2007 standard. 23 Staffs were adequately trained to measure anthropometries and 145 utilized techniques according to WHO guidelines. 24 25 Extreme z-scores deemed biologically 146 implausible (<-6 and > 6 for HAZ, and <-5 and >5 for BAZ) were dropped according to the WHO 147 recommendation. 26 148

Food security 149
Food security was asked differently in wave 1 and 2. In wave 1, respondents were asked 150 whether the household had gotten enough food to eat while in wave 2, they were asked whether 151 the household had experienced any food shortage in the last 12 months. "Yes" in wave 1 and "no" 152 in wave 2 was coded as one indicating that the household was food-secure. 153

Social support 154
Different questions were used to capture social support across waves. In wave 1, only 155 maternal social capital was measured while both maternal and child social support was measured 156 in wave 2. In wave 1, support received from groups in which the mother participated (support 157 from groups) as well as social support received from different types of individuals (support from 158 individuals) were combined into an index of maternal social support. For support from groups, 159 when the respondent answered that they belonged to any of seven different kinds of groups (trade 160 union, community association/co-op, women's group, political group, religious group, 161 credit/funeral group, and sports group), they were subsequently asked whether they had received 162 any support from that group. For support from individual, participants were asked whether they 163 had received support from any of nine different types of individuals (e.g., family, neighbors, 164 friends and so on). A total score of maternal social support was calculated by summing the 165 number of 'yes' resulting in a score range from 0 to 16, which were categorized by median split. 166 In wave 2, only financial support was examined for mothers while child social support was 167 examined comprehensively. Specifically, mothers were asked how many people they could rely 168 for material or financial support with seven response options (none, 1, 2, 3~5, 6~10, 11~15, 16~20, 169

12~30, and >30). Responses were then dichotomized into Yes (none) versus No (all others). 170
Children were asked whether there is someone who can help in six different types of situations 171 (detailed questions were described in Table S1). The overall level of child support was calculated 172 by summing positive responses resulting in a range of 0 ~ 6, which were categorized by median 173 split. Some countries showed a skewed distribution of maternal and child social supports 174 (presented in blue and red arrows in Fig 2.1 and Fig 2.3). We additionally examined financial 175 support for the child based on the question asking whether the child has someone who can help 176 when they needed pocket money (Table S1). 177

Covariates 178
Child characteristics included gender (female vs. male), birth order (2 nd , 3 rd , and higher 179 Household characteristics included household size (5 or 6, and > 6 vs. ≦4), residential location 183 (rural vs. urban), and wealth quintiles (2 nd , 3 rd , 4 th and 5 th vs. 1 st ). Wealth quintile was based on a 184 wealth index ranging from 0 to 1 which was calculated by averaging three variables: housing 185 quality, ownership of consumer durables, and access to services. 186

Statistical analyses 187
First, we summarized the distributions of maternal and child's social support, as well as HAZ and 188 BAZ according to maternal, child, and household characteristics for each of four countries. Then, 189 associations between level of maternal or child's social support and child's HAZ and BAZ at age 190 8 and 12 were assessed using multivariable linear regression models. We introduced the 191 community cluster effect ( 1, 2, 3 ) to the model using the 'cluster' option in 192 the STATA package. The model can be specified as follows; 193 Where X1 includes control variables except for food security, and 1 is a community random effect. 197 Next, to explore the mediating effect of food security in the association between social 198 support and child height and BMI, we fit a meditation model. We examined whether maternal or 199 child social support which showed a significant association with HAZ or BAZ in equation (1) is 200 associated with the probability of having food security, using the following reduced-form 201 specification. 202 Where X 2 includes control variables that have proved to be strongly associated with food 204 security (household size, mother's education, and wealth level). For mediation to be present, in 205 equation (2) needs to be significantly different from 0. Finally, we introduced the food security 206 variable in the equation (1). 207 Where δ in (3) needs to be significantly different from 0 and ′ in (3) is either 0 or less than 210 in (1) in absolute value for mediation to be present. The relations described above can be 211 visualized as a mediation model proposed by Baron and Kenny (Fig 1) 27 . 212 (3)). Mediation analysis was performed using use written code -medeff-in STATA 14. 30-32 228 Analyses were performed separately by wave (age 8 and age 12) and country. 229

230
The pattern of social supports greatly differed between settings (Fig 2). The average 231 number of maternal social supports was highest in Vietnam (3.26), followed by Ethiopia (2.40).    Table S2 shows the descriptive statistics of the study samples at wave 1 from Vietnam, 247 Ethiopia, India, and Peru and the mean HAZ and BAZ for each category (characteristics of study 248 samples at wave 2 hardly changed from wave 1 because the Young Lives data is a cohort survey). 249 Generally, children with higher HAZ/BAZ were more likely to be from households that had fewer 250 household members, were wealthier and more likely to be in an urban area. The average BAZ for 251 the entire sample was remarkably high in Peru compared to other countries in both waves. 252 Table 1. Association between maternal and child support and child z-score for height at wave 1 and 2 in 253 four countries from linear regression adjusted for community cluster effect. The results of the association between maternal and child social support and HAZ at wave 256 1 and 2 were mixed (Table 1). At wave 1 when the child was 8 years old, children of mothers in 257 Vietnam whose overall level of social support belonged to the upper 50% were likely to be lower 258 in HAZ, which was against our expectation. There was no significant association in the other three 259 countries. At wave 2, only Peru showed a positive association between the level of maternal 260 financial support and child's HAZ. Child financial support was negatively associated with HAZ 261 in Ethiopia while it was positively associated in Peru. The overall level of child support showed 262 no association in any countries. As for BAZ, only the level of maternal financial support, 263 operationalized both as a continuous and binary variable, showed a positive association when a 264 child is 12 years old in India (Table 1). 265 268 Table 2 shows results from the linear regression models examining the association 269 between social support and food security. As previously described in the Methods section, we 270 limited the analyses only to the social support variables that showed significant associations with 271 HAZ or BAZ (presented in Table 2). Only the level of maternal financial support in Peru was 272 significantly positively associated with probability of having food security at wave 2. 273

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Finally, causal mediation analysis using Imai et al's method was performed only in Peru, 276 since it was the only country to show a significant association between maternal financial support 277 and food security (Table 3). Our model to test the mediating role of food security in linking 278 maternal financial social support with a child's HAZ in Peru showed that the ACME of upper 50% 279 of maternal financial support is less than zero and statistically non-significant at 95% level, 280 implying that role of food security is not a significant mediator of the impact of maternal financial 281 support on child's height. 282

283
Although there has been much effort to elucidate whether social capital has any beneficial 284 effect on a child's nutritional status, results on the effect of maternal social capital have been mixed 285 across studies depending on the types of social capital, child's age, and global setting. Also, 286 improved food security has been hypothesized as one of the key mechanisms to explain the 287 positive effect of social capital on child anthropometry, but it has never been examined empirically 288 to our knowledge. 289

Limitations 290
There are several limitations to consider when interpreting the results. First, although the 291 YL study is a cohort survey, we could not exploit the longitudinal design for the analyses because 292 social capital was not uniformly measured across the waves. Cross-sectional analysis limits our 293 ability to draw causal inferences. Second, the level of maternal and child social support was 294 arbitrarily categorized. We classified the level of maternal and child social support as being in the 295 upper or lower 50% using median cutoff values, which was our decision to maintain a consistent 296 standard across countries because the distribution of social support differed substantially by 297 country. However, to reduce the possibility of bias from arbitrary operationalization of the 298 variables, we presented results from both models wherein social support was operationalized as 299 both a continuous and a binary variable. Finally, the data for the study is more than 15 years old, 300 which may raise the question of whether the results remain valid under the current context. 301 However, the findings of our study still may offer implications to other LMIC currently 302 undergoing similar contexts of the study countries in the survey years. 303

Interpretation of findings 304
Although social capital has been demonstrated to have a beneficial effect on a range of 305 health outcomes, especially on mental health, the effect of maternal social capital on child 306 anthropometry have been inconsistent. Our results did not support that maternal and child 307 support are strongly or consistently associated with a child's nutritional status. 308 In De Silva's study (2007), the significance of associations between maternal social support 309 and height or weight of children aged between 6 and 18 months varied across four LMICs. 310 Significant associations with a child's height were found between the level of maternal social 311 support in Peru, Vietnam, and Ethiopia. As for child's weight, a significant association was found 312 only in Vietnam. However, unlike our results, the direction was consistently positive, which is 313 assumed to be due to the difference in the age of the study population. Our analyses targeted 314 children aged 8 years old (wave 1) and 12 years old (wave 2) which is much older compared to 315 the sample in De Silva's analysis (2007). Height and weight at a younger age are more sensitive to 316 feeding status or growth stimulation than in the later stage of growth. Evidence shows that catch-317 up growth of preterm infants measured by weight or length mainly occurred from the 10 th to 12 th 318 month of their lives. 33 Another study reported that the catch-up growth of malnutrition of 319 institutionalized children who were adopted before the age of 12 months was much larger than 320 the children adopted after 12 months. 34 Any effect of maternal social support on child's height or 321 BMI are therefore likely to be more pronounced among younger children. 322 There are several suggested mechanisms explaining the positive effect of social support 323 on the child's nutritional status. Social support enables mothers to access knowledge (e.g., how to 324 feed their child for better nutritional status), and to give better care (e.g., practicing hygiene habits 325 or breastfeeding for longer). 35 This effect would be more marked in societies where mothers have 326 a lower background level of education, and therefore, could not have obtained the necessary 327 knowledge through schooling. Emotional support is beneficial for maternal mental health, which 328 also can be linked to improved child growth. 36 37 Martin et al (2004) provided another theory that 329 social capital is associated with reduced odds of household hunger and food insecurity. 16 330 Availability and access to food can be enhanced by collectively sharing information and resources. 331 In a developing country context, sharing seeds and livestock breeds can be one of the examples. 332 Further, in communities with strong ties, solidarity, and networks, people can share the food itself 333 during times of hunger. 19 However, our analyses revealed that the child's nutritional status was 334 associated only with financial support both for mother and child, and food security was not a 335

mediator. 336
There are several possible explanations for the lack of mediation by food insecurity. First, 337 the YL study over-sampled poor sites, and the data from India were collected only in the state of 338 Andhra Pradesh which is one of the poorest states. Therefore, food would not have been sufficient Our findings suggest that interventions to strengthen social support in anticipation of a 351 positive effect on improving child's nutritional status may be unreliable in very poor communities. 352 Also, considering the between-country variability implies that a "one fits all" approach for 353 enhancing social capital may not be appropriate. 354 Despite the several limitations, the present study contributes to our understanding of 355 whether boosting maternal or child social support can be a practical means to improving a child's 356 height and BMI in a resource-poor setting. Future research needs to repeat the current analysis 357 using more sophisticated measurements of social support (i.e., measuring strength and frequency 358 of support) and based on a more recent dataset with a larger sample size to confirm the findings. Strengthening social support within homogenously resource-poor setting may not be a 362 ideal intervention to improve child nutritional status because sources of supports may lack 363 sufficient food resources to share. Considering between-country heterogeneity in association 364 between social support and child nutritional status, a "one size fits all" approach for enhancing 365 social capital may not be appropriate. 366 367 Ethical Approval and consent to participate.

368
Ethical approval was not required as Young Lives Study provides anonymous, secondary data that is 369 publicly available for scientific use. The mediation model. Distribution of social support

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