Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras

Environmental, socioeconomic, and health factors associated with gut microbiome species and strains in isolated Honduras villages

Despite a growing interest in the gut microbiome of non-industrialized countries, data linking deeply sequenced microbiomes from such settings to diverse host phenotypes and situational factors remain uncommon. Using metagenomic data from a community-based cohort of 1,871 people from 19 isolated villages in the Mesoamerican highlands of western Honduras, we report associations between bacterial species and human phenotypes and factors. Among them, socioeconomic factors account for 51.44% of the total associations. Meta-analysis of species-level profiles across several datasets identified several species associated with body mass index, consistent with previous findings. Furthermore, the inclusion of strain-phylogenetic information modifies the overall relationship between the gut microbiome and the phenotypes, especially for some factors like household wealth (e.g., wealthier individuals harbor different strains of Eubacterium rectale). Our analysis suggests a role that gut microbiome surveillance can play in understanding broad features of individual and public health.

The structure and function of antagonistic ties in village social networks

Negative or antagonistic relationships are common in human social networks, but they are less often studied than positive or friendly relationships. The existence of a capacity to have and to track antagonistic ties raises the possibility that they may serve a useful function in human groups. Here, we analyze empirical data gathered from 24,770 and 22,513 individuals in 176 rural villages in Honduras in two survey waves 2.5 y apart in order to evaluate the possible relevance of antagonistic relationships for broader network phenomena. We find that the small-world effect is more significant in a positive world with negative ties compared to an otherwise similar hypothetical positive world without them. Additionally, we observe that nodes with more negative ties tend to be located near network bridges, with lower clustering coefficients, higher betweenness centralities, and shorter average distances to other nodes in the network. Positive connections tend to have a more localized distribution, while negative connections are more globally dispersed within the networks. Analysis of the possible impact of such negative ties on dynamic processes reveals that, remarkably, negative connections can facilitate the dissemination of information (including novel information experimentally introduced into these villages) to the same degree as positive connections, and that they can also play a role in mitigating idea polarization within village networks. Antagonistic ties hold considerable importance in shaping the structure and function of social networks.

Maternal and child health intervention to promote behaviour change: a population-level cluster-randomised controlled trial in Honduras

OBJECTIVES

To assess the efficacy of a sustained educational intervention to affect diverse outcomes across the pregnancy and infancy timeline.

SETTING

A multi-arm cluster-randomised controlled trial in 99 villages in Honduras' Copán region, involving 16 301 people in 5633 households from October 2015 to December 2019.

PARTICIPANTS

Residents aged 12 and older were eligible. A photographic census involved 93% of the population, with 13 881 and 10 263 individuals completing baseline and endline surveys, respectively.

INTERVENTION

22-month household-based counselling intervention aiming to improve practices, knowledge and attitudes related to maternal, neonatal and child health.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcomes were prenatal/postnatal care behaviours, facility births, exclusive breast feeding, parental involvement, treatment of diarrhoea and respiratory illness, reproductive health, and gender/reproductive norms. Secondary outcomes were knowledge and attitudes related to the primary outcomes.

RESULTS

Parents targeted for the intervention were 16.4% (95% CI 3.1%-29.8%, p=0.016) more likely to have their newborn's health checked in a health facility within 3 days of birth; 19.6% (95% CI 4.2%-35.1%, p=0.013) more likely to not wrap a fajero around the umbilical cord in the first week after birth; and 8.9% (95% CI 0.3%-17.5%, p=0.043) more likely to report that the mother breast fed immediately after birth. Changes in knowledge and attitudes related to these primary outcomes were also observed. We found no significant effect on various other practices.

CONCLUSION

A sustained counselling intervention delivered in the home setting by community health workers can meaningfully change practices, knowledge and attitudes related to proper newborn care following birth, including professional care-seeking, umbilical cord care and breast feeding.

TRIAL REGISTRATION NUMBER

NCT02694679.

Induction of social contagion for diverse outcomes in structured experiments in isolated villages

Certain people occupy topological positions within social networks that enhance their effectiveness at inducing spillovers. We mapped face-to-face networks among 24,702 people in 176 isolated villages in Honduras and randomly assigned villages to targeting methods, varying the fraction of households receiving a 22-month health education package and the method by which households were chosen (randomly versus using the friendship-nomination algorithm). We assessed 117 diverse knowledge, attitude, and practice outcomes. Friendship-nomination targeting reduced the number of households needed to attain specified levels of village-wide uptake. Knowledge spread more readily than behavior, and spillovers extended to two degrees of separation. Outcomes that were intrinsically easier to adopt also manifested greater spillovers. Network targeting using friendship nomination effectively promotes population-wide improvements in welfare through social contagion.

Individual-centralized seeding strategy for influence maximization in information-limited networks

Peer effects can directly or indirectly rely on interaction networks to drive people to follow ideas or behaviours triggered by a few individuals, and such effects can be largely improved by targeting the so-called influential individuals. In this article, we study the current most promising seeding strategy used in field experiments, the one-hop strategy, where the underlying interaction networks are generally too impractical or prohibitively expensive to be obtained, and propose an individual-centralized seeding approach to target influential seeds in information-limited networks. The presented strategy works by reasonable follow-up questions to respondents, such as Who do you think has more connections/friends?, and constructs the seeding set by those nodes with the most nominations. In this manner, the proposed method could acquire more information about the studied interaction network from the inference of respondents without surveying additional individuals. We evaluate our strategy on networks from various experimental datasets. Results show that the obtained seeds are much more influential compared to the one-hop strategy and other methods. We also show how the proposed approach could be implemented in field studies and potentially provide better interventions in real scenarios.

Spatiotemporal modeling of under-five mortality and associated risk factors in Ethiopia using 2000-2016 EDHS data

BACKGROUND

The under-five mortality rate serves as a key indicator of the performance of a country's healthcare system. Despite a minor decline, Ethiopia continues to face a persistently high under-five mortality rate across different zones. Thus, this study aimed to identify the risk factors of under-five mortality and the spatiotemporal variation in Ethiopian administrative zones.

METHOD

This study used the 2000-2016 Ethiopian Demographic and Health Survey (EDHS) data which were collected using a two-stage sampling method. A total of 43,029 (10,873 in 2000, 9,861 in 2005, 11,654 in 2011, and 10,641 in 2016) weighted sample under-five child mortality were used. The space-time dynamic model was employed to account for spatial and time effects in 65 administrative zones in Ethiopia.

RESULTS

From the result of a general nesting spatial-temporal dynamic model, there was a significant space-time interaction effect [γ = -0.1444, 95% CI(-0.6680, -0.1355)] for under-five mortality. The increase in the percentages of mothers illiteracy [β = 0.4501, 95% CI (0.2442, 0.6559)], not vaccinated[β= 0.7681, 95% CI (0.5683, 0.9678)], unimproved water[β= 0.5801, CI (0.3793, 0.7808)] were increased death rates for under five children while increased percentage of contraceptive use [β= -0.6609, 95% CI (-0.8636, -0.4582)] and antenatal care unit visit > 4 times [β= -0.1585, 95% CI(-0.1812, -0.1357)] were contributed to the decreased under-five mortality rate at the zone in Ethiopia.

CONCLUSIONS

Even though the mortality rate for children under five has decreased over time, still there is higher in different zones of Ethiopia. There exists spatial and temporal variation in under-five mortality among zones. Therefore, it is very important to consider spatial neighborhood's and temporal context when aiming to avoid under-five mortality.

The enmity paradox

The "friendship paradox" of social networks states that, on average, "your friends have more friends than you do". Here, we theoretically and empirically explore a related and overlooked paradox we refer to as the "enmity paradox". We use empirical data from 24,678 people living in 176 villages in rural Honduras. We empirically show that, for a real negative undirected network (created by symmetrizing antagonistic interactions), the paradox exists as it does in the positive world. Specifically, a person's enemies have more enemies, on average, than a person does. Furthermore, in a mixed world of positive and negative ties, we study the conditions for the existence of the paradox, which we refer to as the "mixed-world paradox", both theoretically and empirically, finding that, for instance, a person's friends typically have more enemies than a person does. We also confirm the "generalized" enmity paradox for non-topological attributes in real data, analogous to the generalized friendship paradox (e.g., the claim that a person's enemies are richer, on average, than a person is). As a consequence, the naturally occurring variance in the degree distribution of both friendship and antagonism in social networks can skew people's perceptions of the social world.

Clinically relevant antibiotic resistance genes are linked to a limited set of taxa within gut microbiome worldwide

The acquisition of antimicrobial resistance (AR) genes has rendered important pathogens nearly or fully unresponsive to antibiotics. It has been suggested that pathogens acquire AR traits from the gut microbiota, which collectively serve as a global reservoir for AR genes conferring resistance to all classes of antibiotics. However, only a subset of AR genes confers resistance to clinically relevant antibiotics, and, although these AR gene profiles are well-characterized for common pathogens, less is known about their taxonomic associations and transfer potential within diverse members of the gut microbiota. We examined a collection of 14,850 human metagenomes and 1666 environmental metagenomes from 33 countries, in addition to nearly 600,000 isolate genomes, to gain insight into the global prevalence and taxonomic range of clinically relevant AR genes. We find that several of the most concerning AR genes, such as those encoding the cephalosporinase CTX-M and carbapenemases KPC, IMP, NDM, and VIM, remain taxonomically restricted to Proteobacteria. Even cfiA, the most common carbapenemase gene within the human gut microbiome, remains tightly restricted to Bacteroides, despite being found on a mobilizable plasmid. We confirmed these findings in gut microbiome samples from India, Honduras, Pakistan, and Vietnam, using a high-sensitivity single-cell fusion PCR approach. Focusing on a set of genes encoding carbapenemases and cephalosporinases, thus far restricted to Bacteroides species, we find that few mutations are required for efficacy in a different phylum, raising the question of why these genes have not spread more widely. Overall, these data suggest that globally prevalent, clinically relevant AR genes have not yet established themselves across diverse commensal gut microbiota.

Estimating the total treatment effect in randomized experiments with unknown network structure

Randomized experiments are widely used to estimate the causal effects of a proposed treatment in many areas of science, from medicine and healthcare to the physical and biological sciences, from the social sciences to engineering, and from public policy to the technology industry. Here we consider situations where classical methods for estimating the total treatment effect on a target population are considerably biased due to confounding network effects, i.e., the fact that the treatment of an individual may impact its neighbors’ outcomes, an issue referred to as network interference or as nonindividualized treatment response. A key challenge in these situations is that the network is often unknown and difficult or costly to measure. We assume a potential outcomes model with heterogeneous additive network effects, encompassing a broad class of network interference sources, including spillover, peer effects, and contagion. First, we characterize the limitations in estimating the total treatment effect without knowledge of the network that drives interference. By contrast, we subsequently develop a simple estimator and efficient randomized design that outputs an unbiased estimate with low variance in situations where one is given access to average historical baseline measurements prior to the experiment. Our solution does not require knowledge of the underlying network structure, and it comes with statistical guarantees for a broad class of models. Due to their ease of interpretation and implementation, and their theoretical guarantees, we believe our results will have significant impact on the design of randomized experiments.

Scaling Up Change: A Critical Review and Practical Guide to Harnessing Social Norms for Climate Action

Anthropogenic carbon emissions have the potential to trigger changes in climate and ecosystems that would be catastrophic for the well-being of humans and other species. Widespread shifts in production and consumption patterns are urgently needed to address climate change. Although transnational agreements and national policy are necessary for a transition to a fully decarbonized global economy, fluctuating political priorities and lobbying by vested interests have slowed these efforts. Against this backdrop, bottom-up pressure from social movements and shifting social norms may offer a complementary path to a more sustainable economy. Furthermore, norm change may be an important component of decarbonization policies by accelerating or strengthening the impacts of other demand-side measures. Individual actions and policy support are social processes—they are intimately linked to expectations about the actions and beliefs of others. Although prevailing social norms often reinforce the status quo and unsustainable development pathways, social dynamics can also create widespread and rapid shifts in cultural values and practices, including increasing pressure on politicians to enact ambitious policy. We synthesize literature on social-norm influence, measurement, and change from the perspectives of psychology, anthropology, sociology, and economics. We discuss the opportunities and challenges for the use of social-norm and social-tipping interventions to promote climate action. Social-norm interventions aimed at addressing climate change or other social dilemmas are promising but no panacea. They require in-depth contextual knowledge, ethical consideration, and situation-specific tailoring and testing to understand whether they can be effectively implemented at scale. Our review aims to provide practitioners with insights and tools to reflect on the promises and pitfalls of such interventions in diverse contexts.

An integrative framework for transformative social change: a case in global wildlife trade

To achieve a sustainable future, it is imperative to transform human actions collectively and underlying social structures. Decades of research in social sciences have offered complementary insights into how such transformations might occur. However, these insights largely remain disjunct and of limited scope, such that strategies for solving global environmental challenges remain elusive. There is a need to integrate approaches focusing on individuals and social structures to understand how individual actions influence and are in turn influenced by social structures and norms. In this paper, we synthesize a range of insights across different schools of thought and integrate them in a novel framework for transformative social change. Our framework explains the relationships among individual behaviors, collective actions, and social structures and helps change agents guide societal transitions toward environmental sustainability. We apply this framework to the global wildlife trade-which presents several distinct challenges of human actions, especially amidst the Covid-19 pandemic-and identify pathways toward transformative change. One key distinction we make is between different individual actions that comprise the practice itself (e.g., buying wildlife products; private action) and those that push for a broader system change in practice (e.g., signaling (dis)approval for wildlife consumption; social-signaling action, and campaigning for policies that end unsustainable wildlife trade; system-changing action). In general, transformative change will require an integrative approach that includes both structural reforms and all three classes of individual action.

Characterizing super-spreaders using population-level weighted social networks in rural communities

Sociocentric network maps of entire populations, when combined with data on the nature of constituent dyadic relationships, offer the dual promise of advancing understanding of the relevance of networks for disease transmission and of improving epidemic forecasts. Here, using detailed sociocentric data collected over 4 years in a population of 24 702 people in 176 villages in Honduras, along with diarrhoeal and respiratory disease prevalence, we create a social-network-powered transmission model and identify super-spreading nodes as well as the nodes most vulnerable to infection, using agent-based Monte Carlo network simulations. We predict the extent of outbreaks for communicable diseases based on detailed social interaction patterns. Evidence from three waves of population-level surveys of diarrhoeal and respiratory illness indicates a meaningful positive correlation with the computed super-spreading capability and relative vulnerability of individual nodes. Previous research has identified super-spreaders through retrospective contact tracing or simulated networks. By contrast, our simulations predict that a node's super-spreading capability and its vulnerability in real communities are significantly affected by their connections, the nature of the interaction across these connections, individual characteristics (e.g. age and sex) that affect a person's ability to disperse a pathogen, and also the intrinsic characteristics of the pathogen (e.g. infectious period and latency). This article is part of the theme issue 'Data science approach to infectious disease surveillance'.

The role and attributes of social networks in the provision of support to women after stillbirth: experiences from Uganda

INTRODUCTION

Communities exert stigma on mothers after stillbirth despite their potential to offer social support to the grieving family. Maternal healthcare-seeking behaviors are socially reinforced rendering a social network approach vital in understanding support dynamics which when utilized can improve community response to mothers experiencing stillbirth. However, the form and direction of social support for women when in need is not clear. The study explored the role and attributes of women's social networks in the provision of support to mothers who have experienced a stillbirth in Uganda.

METHODS

An exploratory cross-sectional study design adopting a social network approach was conducted. Data collection following established procedures was conducted on a convenient sample of 17 mothers who had experienced a stillbirth six months before the study. Frequencies and bivariate analysis were conducted to determine the factors influencing the provision of social support from 293 network members elicited during the alter generation. We then performed a Poisson regression on each of the social support forms and the explanatory variables. Network structure variables were calculated using UCINET version 6 while Netdraw facilitated the visualization of networks.

RESULTS

Overall, social support was available from all network relations mentioned by the respondents. No major variations were observed between the two time periods during pregnancy and following a stillbirth. The most common support received was in form of intangible support such as emotional and information support, mainly from females who were married and from the naturally occurring networks such as family and friends. We also observed that social support followed patterns of network relational characteristics including trust, frequency of contact and alters counted on for support more likely to provide the same.

CONCLUSIONS

A great potential for social support exists within women's social networks to help address stillbirth risk factors during pregnancy and cope after experiencing the same. Alter characteristics like being female, married, and from naturally occurring networks together with relational characteristics such as trust, frequency of contact, and count on alter for support were predictors of eventual social support. Interventions aiming at addressing stillbirth risks at the community level ought to harness these network characteristics for benefits to the mothers.

Using Trellis software to enhance high-quality large-scale network data collection in the field

Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis' ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.

The role of social network support in treatment outcomes for medication for opioid use disorder: A systematic review

BACKGROUND

Social connections can lead to contagion of healthy behaviors. Successful treatment of patients with opioid use disorder may lay in rebuilding social networks. Strong social networks of support can reinforce the benefits of medication treatments that are the current standard of care and the most effective tool physicians have to fight the opioid epidemic.

METHODS

The research team conducted a systematic review of electronic research databases, specialist journals and grey literature up to August 2020 to identify randomized controlled trials of social network support in patient populations receiving medication for opioid use disorder (MOUD). The research team placed the studies into a framework of dynamic social networks, examining the role of networks before MOUD treatment is initiated, during the treatment, and in the long-term following the treatment. The research team analyzed the results across three sources of social network support: partner relationships, family, and peer networks.

RESULTS

Of 5193 articles screened, eight studies were identified as meeting inclusion criteria. Five studies indicated that social network support had a statistically significant effect on improved MOUD treatment outcomes. We find the strongest support for the positive impact of family social network support.

CONCLUSIONS

Social networks significantly shape effectiveness of opioid use disorder treatments. While negative social ties reinforce addiction, positive social support networks can amplify the benefits of medication treatments. Targeted interventions to improve treatment outcomes can be designed and added to MOUD treatment with their effects evaluated in improving patients' odds of recovery from opioid use disorder and reversing the rising trend in opioid deaths.

Social normative and social network factors associated with adolescent pregnancy: a cross-sectional study of 176 villages in rural Honduras

Background

Adolescent pregnancy and childbirth are common throughout Central America. While gendered beliefs promoting motherhood are a known risk factor, their association with adolescent childbirth within the social networks of Central American communities is unknown.

Methods

This was a cross-sectional study looking at adolescent childbirth amongst women ages 15-20 years (N = 2990) in rural Honduras, using reproductive health data on all individuals ≥15 years of age (N = 24 937 of 31 300 population) including social network contacts, all of whom were interviewed as part of the study. The outcome, adolescent childbirth, was defined as having had a child < age 20 years. Predictors included whether a woman’s social contact had an adolescent childbirth and the social contact’s reported perception of community support for adolescent childbirth.

Results

While girls who identified a father in the village as a social contact had a lower likelihood of adolescent childbirth regardless of whether or not they reported being in a partnership, this finding did not hold for girls who identified mothers. There was an association between a social contact’s report of norms supporting adolescent childbirth and a girl’s risk of adolescent childbirth; however, village-level aggregate norms attenuated that relationship. Independent significant associations were found between a girl’s risk of adolescent childbirth and both a social contact’s adolescent childbirth and the village proportion of women who had had an adolescent childbirth. The association between social contacts’ adolescent childbirth and a girl’s risk of adolescent childbirth across relationships was more robust for stronger relationships and when the social contact was closer in age to the girl.

Conclusions

If, as this evidence suggests, a strong driver of adolescent childbirth is the frequency of the occurrence of adolescent childbirth both within the greater community and within a girl’s proximal social network, the challenge for intervention strategies is to encourage norms that prevent adolescent childbirth without stigmatising those who have had an adolescent childbirth. Programmatic efforts to counter prevailing norms that limit a woman’s role to motherhood, and that support and encourage strong norms for girls’ education may play an important role in addressing this situation.

Do village-level normative and network factors help explain spatial variability in adolescent childbearing in rural Honduras?

Adolescent childbearing rates are higher in Central America than almost anywhere else. However, in this research we discovered that adolescent childbearing exhibits variability from one village to another, and we might discover factors associated with this spatial variability that can help us understand key characteristics underlying the pattern of early childbearing. To do this, we assessed the village-level normative and network factors associated with adolescent birth (birth taking place before age 20 years) in rural Honduras and evaluated the geographic dispersion of these patterns. We used full population data from 24,937 people in 176 villages (81% of the eligible population) to assess prevalence and patterns of adolescent childbearing among women. We modeled the predictors of adolescent births among women younger than 21 years. After accounting for individual demographic characteristics, one of the strongest predictors of adolescent birth within the population was village-level collective norms about the acceptability of adolescent childbearing, based on aggregating normative measures from the entire population. The proportion of women in the village who had given birth as an adolescent was also strongly associated with an individual girl's likelihood of having given birth as an adolescent. We used full village-level network analyses to calculate social cohesion within the village. Normative pressure was strongly associated with the likelihood of an adolescent birth in villages with high cohesion (high network density) and was not associated or had a weak association in villages with low cohesion. On the other hand, the longer a girl had lived in the village, the stronger the association between the overall proportion of women in that village who gave birth as adolescents and the girl's own likelihood of having done so. Spatial analyses suggest that levels of adolescent births vary spatially across villages, as do the village-level normative factors associated with them.

Using Social Networks to Understand and Overcome Implementation Barriers in the Global HIV Response

BACKGROUND

Despite the development of several efficacious HIV prevention and treatment methods in the past 2 decades, HIV continues to spread globally. Uptake of interventions is nonrandomly distributed across populations. Such inequality is socially patterned and reinforced by homophily arising from both social selection (becoming friends with similar people) and influence (becoming similar to friends).

METHODS

We conducted a narrative review to describe how social network analysis methods-including egocentric, sociocentric, and respondent-driven sampling designs-provide tools to measure key populations, to understand how epidemics spread, and to evaluate intervention take-up.

RESULTS

Social network analysis-informed designs can improve intervention effectiveness by reaching otherwise inaccessible populations. They can also improve intervention efficiency by maximizing spillovers, through social ties, to at-risk but susceptible individuals. Social network analysis-informed designs thus have the potential to be both more effective and less unequal in their effects, compared with social network analysis-naïve approaches. Although social network analysis-informed designs are often resource-intensive, we believe they provide unique insights that can help reach those most in need of HIV prevention and treatment interventions.

CONCLUSION

Increased collection of social network data during both research and implementation work would provide important information to improve the roll-out of existing studies in the present and to inform the design of more data-efficient, social network analysis-informed interventions in the future. Doing so will improve the reach of interventions, especially to key populations, and to maximize intervention impact once delivered.

The Structure of Negative Social Ties in Rural Village Networks

Negative (antagonistic) connections have been of longstanding theoretical importance for social structure. In a population of 24,696 adults interacting face to face within 176 isolated villages in western Honduras, we measured all connections that were present, amounting to 105,175 positive and 16,448 negative ties. Here, we show that negative and positive ties exhibit many of the same structural characteristics. We then develop a complete taxonomy of all 138 possible triads of two-type relationships. Consistent with balance theory, we find that antagonists of friends and friends of antagonists tend to be antagonists; but, in an important empirical refutation of balance theory, we find that antagonists of antagonists also tend to be antagonists, not friends. Finally, villages with comparable levels of animosity tend to be geographically proximate. Similar processes, involving social contact, give rise to both positive and negative social ties in rural villages, and negative ties play an important role in social structure.

Social network correlates of IPV acceptance in rural Honduras and rural Uganda

We investigated the household-level social network correlates of acceptance of intimate partner violence (IPV) in rural, agrarian settings of Honduras and Uganda, two low-income countries with unequal access to resources based upon gender. We collected complete social network data in each location (Honduras in 2014 and Uganda in 2012), across a diverse range of relationships, and then created a measure of household cohesion by calculating the degree to which members of a household nominated each other as important social connections. Our measure of IPV acceptance was based on 4 questions from the Demographic Health Survey to assess the conditions under which a person believes that it is acceptable for a man to perpetrate physical violence against his wife or partner and we coded a person as positive on IPV acceptance if they answered positively to any of the four questions. We used logistic regression to calculate the odds that an individual accepted IPV given (1) household level cohesion and (2) the proportion of the household that accepts IPV. We found individuals from more cohesive households were less likely to accept IPV controlling for the overall level of IPV acceptance in the household. Nevertheless, those in households more accepting of IPV were more likely to personally accept IPV. In stratified analyses, when household IPV acceptance was especially high, the benefit of household cohesion with respect to IPV was attenuated. The design and implementation of interventions to prevent IPV should consider household structure and norms rather than focusing only on individuals or couples.

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Attitudes towards intimate partner violence are associated with its perpetration.

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Social cohesion has been shown to be protective against violence.

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We look at household cohesion and violence acceptance in Honduras and Uganda.

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Those within socially cohesive household are less likely to accept partner violence.

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This finding depends on the level of violence acceptance within the household.