The business of desire: "Russian" bars in Amman, Jordan.

This paper discusses the type of work migrant women from the former Eastern European countries perform in nightclubs in Amman, Jordan. The fieldwork for this qualitative study was conducted in 2010 and is based on in-depth interviews with 13 women. The topic is approached from the perspective of describing women's choices and journeys to this work. It juxtaposes the sexualised nature of their work with their yearning for a "normal" family life, which they imagine, yet know, is impossible to achieve with the men they meet in their workplaces. Layered on top of these private desires among both women and their clients is the business strategy of the clubs, which operate in the lucrative but marginal space of selling exotic but respectable seduction. I draw on the literature about female migration to the Middle East in order to argue that hostesses in these bars perform affective labour akin to care work, within the neoliberal global economy that individualises risk

Advancing the frontiers of geographic accessibility to healthcare services

Assessing geographic accessibility to healthcare is essential to identify communities that have been left behind. Smartphone mobility data now enables the study of healthcare accessibility over a global scale, providing estimates of actual travel times to access care

Interventions to maintain essential services for maternal, newborn, child, and adolescent health during the COVID-19 pandemic: a scoping review of evidence from low- and middle-income countries

Background: The coronavirus disease 2019 (COVID-19) pandemic had challenged health systems worldwide, including those in low- and middle-income countries (LMICs). Aside from measures to control the pandemic, efforts were made to continue the provision and use of essential services. At that time, information was not organised and readily available to guide country-level decision-making. This review aims to summarise evaluated interventions to maintain essential services for maternal, newborn, child, and adolescent health in response to COVID-19 in LMICs, in order to learn from the interventions and facilitate their use in the next disruption. Methods: We conducted a scoping review by Embase, MEDLINE, and Global Health for literature published between 1 January 2020 and 26 December 2022, without restrictions for language. We extracted information about the setting, population targeted, service type, intervention, and evaluation from the included studies and summarised it both quantitatively and narratively. Results: We retrieved 11 395 unique references and included 30 studies describing 32 evaluated interventions. Most interventions (84%) were implemented in 2020, with a median duration of five months (interquartile range (IQR) = 3-8), and were conducted in Africa (34%) or Southeast Asia (31%). Interventions focussed on maintaining services for maternal and newborn health (56%) or children and adolescents (56%) were most common. Interventions aimed to address problems related to access (94%), fear (31%), health workers shortage (25%), and vulnerability (22%). Types of interventions included telehealth (69%), protocols/guidelines to adapt care provision (56%), and health education (40%); a few entailed health worker training (16%). The described interventions were mostly led by the public (56%) or non-profit (34%) sectors. Methodologies of their evaluations were heterogeneous; the majority used quantitative methods, had a prospective research design, and used output- and outcome-based indicators. Conclusions: In this review, we identified an important and growing body of evidence of evaluated interventions to maintain essential services for maternal, newborn, child, and adolescent health during COVID-19 in LMICs. To improve preparedness and responsiveness for future disruptions, managers for decision-makers in LMICs could benefit from up-to-date inventories describing implemented interventions and evaluations to facilitate evidence-based implementation of strategies, as well as tools for conducting optimal quality operational and implementation research during disruptions (e.g. rapid ethical approvals, access to routine data)

Neonatal and perinatal mortality in the urban continuum:A geospatial analysis of the household survey, satellite imagery and travel time data in Tanzania

Introduction Neonatal mortality might be higher in urban areas. This paper aims to minimize challenges related to misclassification of neonatal deaths and stillbirths, and oversimplification of the variation in urban environments to accurately estimate the direction and strength of the association between urban residence and neonatal/perinatal mortality in Tanzania. Methods The Tanzania Demographic and Health Survey (DHS) 2015-16 was used to assess birth outcomes for 8,915 pregnancies among 6,156 women of reproductive age, by urban or rural categorization in the DHS and based on satellite imagery. The coordinates of 527 DHS clusters were spatially overlaid with the 2015 Global Human Settlement Layer, showing the degree of urbanisation based on built environment and population density. A three-category urbanicity measure (core urban, semi-urban, and rural) was defined and compared to the binary DHS measure. Travel time to the nearest hospital was modelled using least-cost path algorithm for each cluster. Bivariate and multi-level multivariable logistic regression models were constructed to explore associations between urbanicity and neonatal/perinatal deaths. Results Both perinatal and neonatal mortality rates were highest in core urban and lowest in rural clusters. Bivariate models showed higher odds of neonatal death (OR=1.85; 95% CI: 1.12, 3.08) and perinatal death (OR=1.60; 95% CI 1.12, 2.30) in core urban compared to rural clusters. In multivariable models, these associations had the same direction and size, but were no longer statistically significant. Travel time to nearest hospital was not associated with neonatal or perinatal mortality. Conclusion Addressing the higher rates of neonatal and perinatal mortality in densely populated urban areas is critical for Tanzania to meet national and global reduction targets. Urban populations are diverse, and certain neighbourhoods or sub-groups may be disproportionately affected by poor birth outcomes. Research must sample within and across urban areas to differentiate, understand and minimize risks specific to urban settings. Key questions What is already known? - Urban advantage in health outcomes has been questioned, both for adult and child mortality - An analysis of neonatal mortality using Demographic and Health Survey data in Tanzania in 2015-16 showed double risk in urban compared to rural areas - This phenomenon might be occurring in other sub-Saharan African countries What are the new findings? - Categorisation of locations as urban or rural on the 2015-16 Demographic and Health Survey in Tanzania is both simplistic and inaccurate - Risks of neonatal and perinatal mortality are highest in core, densely populated urban areas in mainland Tanzania, and lowest in rural areas - Travel time to nearest public hospital was not associated with neonatal or perinatal mortality in mainland Tanzania What do the new findings imply? - Extent of urbanicity as an exposure follows a spectrum and needs to be measured and understood as such - Explanatory models specific to neonatal and perinatal mortality in core urban areas are urgently needed to guide actions toward reducing existing high rate - Known risk factors such as anaemia and young maternal age continue to play a role in neonatal and perinatal mortality and must be urgently addressed

Maternal exposure to intimate partner violence and breastfeeding practices of children 0–23 months: findings from the 2018 Nigeria Demographic and Health Survey

Background: Intimate partner violence (IPV) is an important public health and human rights issue with high prevalence in Nigeria. Understanding the link between IPV and breastfeeding—an important intervention to reduce child morbidity and mortality—is critical and could inform strategies to promote breastfeeding and reduce IPV. This study examines the association between recent maternal experience of IPV and optimal breastfeeding of children aged 0 to 23 months in Nigeria. Methods: This secondary analysis of the 2018 Nigeria Demographic and Health Survey included a sample of 3,749 women aged 15 – 49 years who had singleton live birth in the two years preceding the survey. The outcome variable was optimal breastfeeding for age (exclusive breastfeeding in the first six months of life and any breastfeeding from 6-23 months). We defined recent IPV as exposure to any IPV in the 12 months preceding the survey; we also included the number of forms of IPV experienced (0, 1, 2 or 3: physical, emotional, and sexual) as an additional categorical independent variable. We used frequencies and proportions to describe key variables. We then conducted two multivariable logistic regression models—with any IPV and number of forms of IPV to determine the crude and adjusted odds ratios between IPV and optimal breastfeeding for age. Results: Among all women, 31% experienced any IPV and 2.6% all three forms. Nearly one-third (31.7%) of babies <6 months of age and 70.4% of 6–23-month-olds were optimally breastfed. We found no significant association between any IPV and optimal breastfeeding for age (adjusted odds ratio, aOR=0.92; 95% confidence interval, CI=0.76–1.14). However, women who experienced all three forms of IPV were significantly less likely to optimally breastfeed their children (aOR=0.58; 95% CI =0.36–0.93) than those with no IPV experience. Conclusions: Policies and strategies to promote breastfeeding should include measures to identify and mitigate IPV against pregnant and breastfeeding women and provide optimal psychological and breastfeeding support for those who are victims of IPV

No increase in use of hospitals for childbirth in Tanzania over 25 years: Accumulation of inequity among poor, rural, high parity women.

Improving childbirth care in rural settings in sub-Saharan Africa is essential to attain the commitment expressed in the Sustainable Development Goals to leave no one behind. In Tanzania, the period between 1991 and 2016 was characterized by health system expansion prioritizing primary health care and a rise in rural facility births from 45% to 54%. Facilities however are not all the same, with advanced management of childbirth complications generally only available in hospitals and routine childbirth care in primary facilities. We hypothesized that inequity in the use of hospital-based childbirth may have increased over this period, and that it may have particularly affected high parity (≥5) women. We analysed records of 16,080 women from five Tanzanian Demographic and Health Surveys (1996, 1999, 2004, 2010, 2015/6), using location of the most recent birth as outcome (home, primary health care facility or hospital), wealth and parity as exposure variables and demographic and obstetric characteristics as potential confounders. A multinomial logistic regression model with wealth/parity interaction was run and post-estimation margins analysis produced percentages of births for various combinations of wealth and parity for each survey. We found no reduction in inequity in this 25-year period. Among poorest women, lowest use of hospital-based childbirth (around 10%) was at high parity, with no change over time. In women having their first baby, hospital use increased over time but with a widening pro-rich gap (poorest women predicted use increased from 36 to 52% and richest from 40 to 59%). We found that poor rural women of high parity were a vulnerable group requiring specifically targeted interventions to ensure they receive effective childbirth care. To leave no one behind, it is essential to look beyond the average coverage of facility births, as such a limited focus masks different patterns and time trends among marginalised groups

Inequalities in geographical access to emergency obstetric and newborn care.

In 2020, an estimated 287 000 women died due to complications of pregnancy and childbirth, while 1.9 million still-births occurred in 2021. As many as half of maternal deaths and three in four stillbirths are preventable if women can access timely emergency care that is provided by skilled health personnel.(1) To date, efforts of the global community to reduce maternal mortality and stillbirths have mostly focused on ensuring the availability of emergency obstetric and newborn care, minimizing financial barriers to care and, more recently, improving care quality. However, governments have given less attention to geographical accessibility and inequalities in access between and within populations. Pregnant women in low- and middle-income countries often need to seek care on their own, even in emergencies, and many face immense challenges in reaching emergency obstetric and newborn care facilities.(2) Here we examine the geographical accessibility to emergency obstetric and newborn care in low- and middle-income settings. We argue for the use of emerging scientific evidence and contextual understanding to better identify priority problem areas, select appropriate methods, and develop solutions and targets related to assessing geographical accessibility for emergency obstetric and newborn care

Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations

Google Maps Directions Application Programming Interface (the API) and AccessMod tools are increasingly being used to estimate travel time to healthcare. However, no formal comparison of estimates from the tools has been conducted. We modelled and compared median travel time (MTT) to comprehensive emergency obstetric care (CEmOC) using both tools in three Nigerian conurbations (Kano, Port-Harcourt, and Lagos). We compiled spatial layers of CEmOC healthcare facilities, road network, elevation, and land cover and used a least-cost path algorithm within AccessMod to estimate MTT to the nearest CEmOC facility. Comparable MTT estimates were extracted using the API for peak and non-peak travel scenarios. We investigated the relationship between MTT estimates generated by both tools at raster celllevel (0.6 km resolution). We also aggregated the raster cell estimates to generate administratively relevant ward-level MTT. We compared ward-level estimates and identified wards within the same conurbation falling into different 15-minute incremental categories (<15/15-30/30-45/45-60/+60). Of the 189, 101 and 375 wards, 72.0%, 72.3% and 90.1% were categorised in the same 15- minute category in Kano, Port-Harcourt, and Lagos, respectively. Concordance decreased in wards with longer MTT. AccessMod MTT were longer than the API’s in areas with ≥45min. At the raster cell-level, MTT had a strong positive correlation (≥0.8) in all conurbations. Adjusted R2 from a linear model (0.624-0.723) was high, increasing marginally in a piecewise linear model (0.677-0.807). In conclusion, at <45-minutes, ward-level estimates from the API and AccessMod are marginally different, however, at longer travel times substantial differences exist, which are amenable to conversion factors

Increasing prevalence of overweight and obesity among Tanzanian women of reproductive age intending to conceive: evidence from three Demographic Health Surveys, 2004-2016

# Background The prevalence of people who are overweight or obese is increasing globally, especially in low- and middle-income countries. High body mass index (BMI) among women of reproductive age is a risk factor for various adverse reproductive and pregnancy outcomes. This study aims to describe trends over time in the distribution of BMI among Tanzanian women of reproductive age intending to conceive between 2004/5 and 2015/16, and identify factors associated with high BMI. # Methods We used data on 20,819 women of reproductive age (15-49 years) intending to conceive who participated in the Tanzania Demographic and Health Surveys in 2004/5, 2010 and 2015/16. We estimated the prevalence of high BMI (being overweight \[≥25 to <30 kg/m^2^] and obesity \[≥30kg/m^2^) and trends in the prevalence of high BMI across the three surveys. Using survey-weighted multivariable logistic regression, we used the most recent 2015/16 survey data to identify factors associated with high BMI. # Results Median BMI increased from 21.7kg/m^2^ (inter-quartile range, IQR=19.9-24.1 kg/m^2^) in 2004/5 to 22.0 kg/m^2^ (IQR=20.0-24.8 kg/m^2^) in 2010 to 22.7 kg/m^2^ (IQR=20.4-26.0 kg/m^2^) in 2015/16. The prevalence of overweight women increased from 11.1% in 2004/5 to 15.8% in 2015 (P <0.001). The prevalence of obesity increased from 3.1% in 2004/5 to 8.0% in 2015/16 (P<0.001). Women in the highest wealth quintile had higher odds (adjusted odds ratio, aOR= 4.5; 95%CI 3.4-6.3, P<0.001) of high BMI than women in the lowest quintile. The odds of high BMI were about four times greater (aOR=3.9; 95%CI=2.9-5.4, P<0.001) for women 40-44 years compared to 20–24-year-olds. Women in the high-paying occupations had greater odds of high BMI than those working in agriculture (aOR=1.5; 95% CI=1.1-2.2, P=0.002). Women residing in the Southern zone had 1.9 (95%CI=1.5-2.5, P<0.001) greater odds of high BMI than Lake zone residents. # Conclusions In Tanzania, high BMI affects almost 1 in 4 women of reproductive age who intend to conceive. This contributes to the burden of poor maternal and reproductive health outcomes. We recommend developing and implementing health-system strategies for addressing high BMI, tailored to the modifiable risk factors identified among women of reproductive age

Developing policy-ready digital dashboards of geospatial access to emergency obstetric care: a survey of policymakers and researchers in sub-Saharan Africa

Background Dashboards are increasingly being used in sub-Saharan Africa (SSA) to support health policymaking and governance. However, their use has been mostly limited to routine care, not emergency services like emergency obstetric care (EmOC). To ensure a fit-for-purpose dashboard, we conducted an online survey with policymakers and researchers to understand key considerations needed for developing a policy-ready dashboard of geospatial access to EmOC in SSA. Methods Questionnaires targeting both stakeholder groups were pre-tested and disseminated in English, French, and Portuguese across SSA. We collected data on participants’ awareness of concern areas for geographic accessibility of EmOC and existing technological resources used for planning of EmOC services, the dynamic dashboard features preferences, and the dashboard's potential to tackle lack of geographic access to EmOC. Questions were asked as multiple-choice, Likert-scale, or open-ended. Descriptive statistics were used to summarise findings using frequencies or proportions. Free-text responses were recoded into themes where applicable. Results Among the 206 participants (88 policymakers and 118 researchers), 90% reported that rural areas and 23% that urban areas in their countries were affected by issues of geographic accessibility to EmOC. Five percent of policymakers and 38% of researchers were aware of the use of maps of EmOC facilities to guide planning of EmOC facility location. Regarding dashboard design, most visual components such as location of EmOC facilities had almost universal desirability; however, there were some exceptions. Nearly 70% of policymakers considered the socio-economic status of the population and households relevant to the dashboard. The desirability for a heatmap showing travel time to care was lower among policymakers (53%) than researchers (72%). Nearly 90% of participants considered three to four data updates per year or less frequent updates adequate for the dashboard. The potential usability of a dynamic dashboard was high amongst both policymakers (60%) and researchers (82%). Conclusion This study provides key considerations for developing a policy-ready dashboard for EmOC geographical accessibility in SSA. Efforts should now be targeted at establishing robust estimation of geographical accessibility metrics, integrated with existing health system data, and developing and maintaining the dashboard with up-to-date data to maximise impact in these settings