Unequal power relations and partner violence against women in Tanzania: a cross-sectional analysis.

BACKGROUND: Research on factors associated with partner violence against women is often framed within the context of gender inequality and power imbalances between husbands and wives-inequalities that are considered products of broader structural systems. Tanzania, a patriarchal society where high levels of partner violence exists, has gone through rapid economic and social changes over the past two decades. Increasing numbers of women are seeking paid work, and men's ideals of manhood have reshaped with evidence of extra marital relations and alcohol use. Nationally representative population-based data documents 46.2% of ever-married women have experienced physical or sexual partner violence in their lifetime; 29.6% in the past year. In order to plan appropriate interventions to end violence against women, factors consistently associated with abuse need to be understood. METHODS: This study uses "couples" data from the 2015 Tanzania Demographic and Health Survey to examine correlates of past year partner violence against women. Multivariate regression analysis was used to explore individual and relational-level variables-including socio-demographic characteristics and history of abuse among women, partner behavioural characteristics, and indicators of gender and economic inequality-among 1278 married and cohabiting couples. RESULTS: At the individual level, women's experiences of non-partner violence (sexual abuse by a non-partner and witnessing violence in childhood) was strongly associated with risk and highlights that all forms of violence against women serve to keep them subordinated. Partner behavioural characteristics (polygamy and problematic alcohol use) were also associated with risk. Household socio-economic status, however, was not significantly associated with women's risk in the final multivariate model. At the relational-level, men's age difference of 10 or more years; and any employment (compared to none/unpaid) were associated with lower risk. When considering attitudes tolerant towards wife abuse, the strongest association with risk of violence was when both partners held tolerant views. CONCLUSION: The findings support the assertions of violence being associated with women's prior/additional experiences of abuse and with men's harmful expressions of masculinity. In addition to interventions that focus on transforming gender norms and attitudes (at the individual and community levels), addressing economic, legal and political structural barriers are also required

Risk factors for violence against women in high-prevalence settings: a mixed-methods systematic review and meta-synthesis

INTRODUCTION: Violence against women (VAW) affects one in three women globally. In some countries, women are at much higher risk. We examined risk factors for VAW in countries with the highest 12-month prevalence estimates of intimate partner violence (IPV) to develop understanding of this increased risk. METHODS: For this systematic review, we searched PUBMED, CINAHL, PROQUEST (Middle East and North Africa; Latin America and Iberia; East and South Asia), Web of Science, EMBASE and PsycINFO (Ovid) for records published between 1 January 2000 and 1 January 2021 in English, French and Spanish. Included records used quantitative, qualitative, or mixed-methods, reported original data, had VAW as the main outcome, and focused on at least one of 23 countries in the highest quintile of prevalence figures for women's self-reported experiences of physical and/or sexual violence in the past 12 months. We used critical interpretive synthesis to develop a conceptual model for associations between identified risk factors and VAW. RESULTS: Our search identified 12 044 records, of which 241 were included for analysis (2 80 360 women, 40 276 men, 274 key informants). Most studies were from Bangladesh (74), Uganda (72) and Tanzania (43). Several quantitative studies explored community-level/region-level socioeconomic status and education as risk factors, but associations with VAW were mixed. Although fewer in number and representing just one country, studies reported more consistent effects for community-level childhood exposure to violence and urban residence. Theoretical explanations for a country's high prevalence point to the importance of exposure to other forms of violence (armed conflict, witnessing parental violence, child abuse) and patriarchal social norms. CONCLUSION: Available evidence suggests that heightened prevalence of VAW is not attributable to a single risk factor. Multilayered and area-level risk analyses are needed to ensure funding is appropriately targeted for countries where VAW is most pervasive. PROSPERO REGISTRATION NUMBER: The review is registered with PROSPERO (CRD42020190147)

What factors are associated with recent intimate partner violence? findings from the WHO multi-country study on women's health and domestic violence

<p>Abstract</p> <p>Background</p> <p>Intimate partner violence (IPV) against women is a global public health and human rights concern. Despite a growing body of research into risk factors for IPV, methodological differences limit the extent to which comparisons can be made between studies. We used data from ten countries included in the WHO Multi-country Study on Women's Health and Domestic Violence to identify factors that are consistently associated with abuse across sites, in order to inform the design of IPV prevention programs.</p> <p>Methods</p> <p>Standardised population-based household surveys were done between 2000 and 2003. One woman aged 15-49 years was randomly selected from each sampled household. Those who had ever had a male partner were asked about their experiences of physically and sexually violent acts. We performed multivariate logistic regression to identify predictors of physical and/or sexual partner violence within the past 12 months.</p> <p>Results</p> <p>Despite wide variations in the prevalence of IPV, many factors affected IPV risk similarly across sites. Secondary education, high SES, and formal marriage offered protection, while alcohol abuse, cohabitation, young age, attitudes supportive of wife beating, having outside sexual partners, experiencing childhood abuse, growing up with domestic violence, and experiencing or perpetrating other forms of violence in adulthood, increased the risk of IPV. The strength of the association was greatest when both the woman and her partner had the risk factor.</p> <p>Conclusions</p> <p>IPV prevention programs should increase focus on transforming gender norms and attitudes, addressing childhood abuse, and reducing harmful drinking. Development initiatives to improve access to education for girls and boys may also have an important role in violence prevention.</p

Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets

<p>Abstract</p> <p>Background</p> <p>The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phenotypes. The immense potential offered by these data derives from the fact that genotypic variation is the sole source of perturbation and can therefore be used to reconcile changes in gene expression programs with the parental genotypes. To date, several methodologies have been developed for modeling eQTL data. These methods generally leverage genotypic data to resolve causal relationships among gene pairs implicated as associates in the expression data. In particular, leading studies have augmented Bayesian networks with genotypic data, providing a powerful framework for learning and modeling causal relationships. While these initial efforts have provided promising results, one major drawback associated with these methods is that they are generally limited to resolving causal orderings for transcripts most proximal to the genomic loci. In this manuscript, we present a probabilistic method capable of learning the causal relationships between transcripts at all levels in the network. We use the information provided by our method as a prior for Bayesian network structure learning, resulting in enhanced performance for gene network reconstruction.</p> <p>Results</p> <p>Using established protocols to synthesize eQTL networks and corresponding data, we show that our method achieves improved performance over existing leading methods. For the goal of gene network reconstruction, our method achieves improvements in recall ranging from 20% to 90% across a broad range of precision levels and for datasets of varying sample sizes. Additionally, we show that the learned networks can be utilized for expression quantitative trait loci mapping, resulting in upwards of 10-fold increases in recall over traditional univariate mapping.</p> <p>Conclusions</p> <p>Using the information from our method as a prior for Bayesian network structure learning yields large improvements in accuracy for the tasks of gene network reconstruction and expression quantitative trait loci mapping. In particular, our method is effective for establishing causal relationships between transcripts located both proximally and distally from genomic loci.</p

Improving epidemiologic data analyses through multivariate regression modelling

Regression modelling is one of the most widely utilized approaches in epidemiological analyses. It provides a method of identifying statistical associations, from which potential causal associations relevant to disease control may then be investigated. Multivariable regression – a single dependent variable (outcome, usually disease) with multiple independent variables (predictors) – has long been the standard model. Generalizing multivariable regression to multivariate regression – all variables potentially statistically dependent – offers a far richer modelling framework. Through a series of simple illustrative examples we compare and contrast these approaches. The technical methodology used to implement multivariate regression is well established – Bayesian network structure discovery – and while a relative newcomer to the epidemiological literature has a long history in computing science. Applications of multivariate analysis in epidemiological studies can provide a greater understanding of disease processes at the population level, leading to the design of better disease control and prevention programs

Measuring the health-related Sustainable Development Goals in 188 countries : a baseline analysis from the Global Burden of Disease Study 2015

Background In September, 2015, the UN General Assembly established the Sustainable Development Goals (SDGs). The SDGs specify 17 universal goals, 169 targets, and 230 indicators leading up to 2030. We provide an analysis of 33 health-related SDG indicators based on the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015). Methods We applied statistical methods to systematically compiled data to estimate the performance of 33 health-related SDG indicators for 188 countries from 1990 to 2015. We rescaled each indicator on a scale from 0 (worst observed value between 1990 and 2015) to 100 (best observed). Indices representing all 33 health-related SDG indicators (health-related SDG index), health-related SDG indicators included in the Millennium Development Goals (MDG index), and health-related indicators not included in the MDGs (non-MDG index) were computed as the geometric mean of the rescaled indicators by SDG target. We used spline regressions to examine the relations between the Socio-demographic Index (SDI, a summary measure based on average income per person, educational attainment, and total fertility rate) and each of the health-related SDG indicators and indices. Findings In 2015, the median health-related SDG index was 59.3 (95% uncertainty interval 56.8-61.8) and varied widely by country, ranging from 85.5 (84.2-86.5) in Iceland to 20.4 (15.4-24.9) in Central African Republic. SDI was a good predictor of the health-related SDG index (r(2) = 0.88) and the MDG index (r(2) = 0.2), whereas the non-MDG index had a weaker relation with SDI (r(2) = 0.79). Between 2000 and 2015, the health-related SDG index improved by a median of 7.9 (IQR 5.0-10.4), and gains on the MDG index (a median change of 10.0 [6.7-13.1]) exceeded that of the non-MDG index (a median change of 5.5 [2.1-8.9]). Since 2000, pronounced progress occurred for indicators such as met need with modern contraception, under-5 mortality, and neonatal mortality, as well as the indicator for universal health coverage tracer interventions. Moderate improvements were found for indicators such as HIV and tuberculosis incidence, minimal changes for hepatitis B incidence took place, and childhood overweight considerably worsened. Interpretation GBD provides an independent, comparable avenue for monitoring progress towards the health-related SDGs. Our analysis not only highlights the importance of income, education, and fertility as drivers of health improvement but also emphasises that investments in these areas alone will not be sufficient. Although considerable progress on the health-related MDG indicators has been made, these gains will need to be sustained and, in many cases, accelerated to achieve the ambitious SDG targets. The minimal improvement in or worsening of health-related indicators beyond the MDGs highlight the need for additional resources to effectively address the expanded scope of the health-related SDGs.Peer reviewe

Geographical variations in the prevalence of HIV and other sexually transmitted infections in rural Tanzania.

The prevalence and incidence of HIV and other sexually transmitted infections (STIs) were recorded in two lake-island and eight rural mainland communities in Mwanza, Tanzania. The prevalence and incidence of HIV and syphilis were lower on the islands, but this pattern was not seen for herpes simplex virus type-2, gonorrhoea, chlamydia, male urethritis or antenatal prevalences of Trichomonas vaginalis. Island men reported fewer sexual partners than mainland men but no differences were found for women. Island men were more likely to be circumcised, island women less mobile and there were differences in marriage patterns. Possible explanations for the differences in HIV and syphilis include: slower introduction of HIV into the islands because of geographical isolation, more core-group sexual contact on the mainland, higher prevalence of male circumcision on the islands and differences in marital status. Differences in transmission dynamics may lead to geographical patterns that vary between STIs

Exploring the association between women's access to economic resources and intimate partner violence in Dar es Salaam and Mbeya, Tanzania.

The relationship between women's access to economic resources, e.g. employment or access to micro-credit, and experience of intimate partner violence is complex. Empirical evidence documents that in some settings women's employment is associated with higher risk of partner violence but in other settings with lower risk. Evidence also shows that these conflicting associations exist not only between countries but also within different country settings. Using two population-based data sets gathered in 2002 in contrasting Tanzania settings-Dar es Salaam and Mbeya-, we used multivariate logistic regression to examine the relationship between women's access to economic resources and partner violence. Two indicators of economic resources were examined: whether women earned money and whether women owned a business either with someone or exclusively. In Dar es Salaam we found evidence of a higher risk association among women who earned money and who owned a business exclusively by themselves and a lower risk association among women who owned a business with someone. We found no relationship between either indicator of economic resources and partner violence in Mbeya. Other factors were similarly associated with partner violence in both settings and the strongest associations found were related to the respondents' partners: refusal to give money; alcohol use and relationships with other women. The findings support the assertion that women's access to economic resources operate differently in different country settings, thus highlighting the need for targeted prevention efforts that are relevant for the context

Interviewer Training in the WHO Multi-Country Study on Women’s Health and Domestic Violence

The importance of a sound research strategy for measuring and understanding violence against women cross-culturally is well recognized. However, the value of specialized interviewer training to attain these data is not always fully appreciated. This article describes interviewer selection and training in the World Health Organization (WHO) Multi-Country Study on Women’s Health and Domestic Violence and highlights their importance. Such training ensures high-quality data and cross-country comparability, protects the safety of respondents and interviewers, and increases the impact of the study. Moreover, women are not only willing to share experiences with trained and empathetic interviewers but also find the interview a positive experience. </jats:p