UNASSIGNED: Existing estimates of rates of childhood disability in Kenya are based on data with important limitations. Individual-level data on childhood disability at the local level is also lacking, leaving critical knowledge gaps for clinical and programmatic development.
UNASSIGNED: We aimed to estimate the rates of children at-risk for disability, examine the external factors related to risk of childhood disability, and gain a better understanding of the challenges experienced by children at-risk for disabilities and their families within western Kenya.
UNASSIGNED: We conducted a small, cross-sectional randomized community survey to assess the rates of childhood disability across six administrative locations in Uasin Gishu County, Kenya, and to understand the experiences of these children and their caretakers.
UNASSIGNED: Rate of childhood disability in Uasin Gishu county was estimated to be 5%, with the most common disabilities being mood disorders. Caretakers reported several barriers to accessing treatment for their children at-risk of having disabilities, including financial concerns and lack of transportation.
UNASSIGNED: Our findings suggest a need for improved access to care in this region, including addressing significant barriers to accessing care such as stigma and socioeconomic challenges. These community-level data will inform the development of future infrastructure and programming for this population.

Critical infrastructures are ubiquitous and their interdependencies have become more complex leading to their uncertain behaviors in the aftermath of disasters. The article develops an integrated economic input-output model that incorporates household-level survey data from Hurricane Sandy, which made its landfall in 2012. In this survey, 427 respondents who were living in the state of New Jersey during Hurricane Sandy were used in the study. The integration of their responses allowed us to show the probability and duration of various types of critical infrastructure failures due to a catastrophic hurricane event and estimate the economic losses across different sectors. The percentage of disruption and recovery period for various infrastructure systems were extracted from the survey, which were then utilized in the economic input-output model comprising of 71 economic sectors. Sectors were then ranked according to: (i) inoperability, the percentage in which a sector is disrupted relative to its ideal level, and (ii) economic loss, the monetary worth of business interruption caused by the disaster. With the combined infrastructure disruptions in the state of New Jersey, the model estimated an economic loss of $36 billion, which is consistent with published estimates. Results from this article can provide insights for future disaster preparedness and resilience planning.

Background: The coexistence of stunting and wasting in a child increases the risk of mortality and requires more intensive treatment and care. However, there is limited research on the burden of concurrent stunting and wasting among children and the socioeconomic factors that are correlated with having both conditions. Aim: To understand the prevalence and sociodemographic correlates of stunting, wasting, and concurrent stunting and wasting among a sample of children ages 6-144 months experiencing poverty in the Philippines. Methods: Cross-sectional data were drawn from nutrition screening and sociodemographic surveys conducted by International Care Ministries in 2018-2019. Descriptive statistics were calculated to determine the prevalence of stunting, wasting, and concurrent stunting and wasting. Multilevel logistic regression modelling was conducted to understand the sociodemographic factors that were associated with stunting and wasting. Results: Among the 3005 children in this sample, the prevalence of stunting, wasting, and concurrent stunting and wasting was 49.9%, 9.3%, and 4.6%, respectively. Children experiencing concurrent stunting and wasting lived in households in lower wealth index quintiles, had a household head with fewer years of education, and were more likely to experience food insecurity compared to children who were not stunted or wasted. The education of the household head, the number of household members, and the wealth of the household were correlated with stunting across age groups, while food insecurity was correlated with wasting among younger children. Conclusion: The presence of concurrent stunting and wasting among children provides the impetus to integrate both conditions into nutrition monitoring, prevention, and treatment interventions.

The ideal approach for calculating effective coverage of health services using ecological linking requires accounting for variability in facility readiness to provide health services and patient volume by incorporating adjustments for facility type into estimates of facility readiness and weighting facility readiness estimates by service-specific caseload. The aim of this study is to compare the ideal caseload-weighted facility readiness approach to two alternative approaches: (1) facility-weighted readiness and (2) observation-weighted readiness to assess the suitability of each as a proxy for caseload-weighted facility readiness. We utilised the 2014-2015 Tanzania Service Provision Assessment along with routine health information system data to calculate facility readiness estimates using the three approaches. We then conducted equivalence testing, using the caseload-weighted estimates as the ideal approach and comparing with the facility-weighted estimates and observation-weighted estimates to test for equivalence. Comparing the facility-weighted readiness estimates to the caseload-weighted readiness estimates, we found that 58% of the estimates met the requirements for equivalence. In addition, the facility-weighted readiness estimates consistently underestimated, by a small percentage, facility readiness as compared to the caseload-weighted readiness estimates. Comparing the observation-weighted readiness estimates to the caseload-weighted readiness estimates, we found that 64% of the estimates met the requirements for equivalence. We found that, in this setting, both facility-weighted readiness and observation-weighted readiness may be reasonable proxies for caseload-weighted readiness. However, in a setting with more variability in facility readiness or larger differences in facility readiness between low caseload and high caseload facilities, the observation-weighted approach would be a better option than the facility-weighted approach. While the methods compared showed equivalence, our results suggest that selecting the best method for weighting readiness estimates will require assessing data availability alongside knowledge of the country context.

Cross-sectional studies have found a relationship between social media use and depression and anxiety in young people. However, few longitudinal studies using representative data and mediation analysis have been conducted to understand the causal pathways of this relationship.
This study aims to examine the longitudinal relationship between social media use and young people\'s mental health and the role of self-esteem and social connectedness as potential mediators.
The sample included 3228 participants who were 10- to 15-year-olds from Understanding Society (2009-2019), a UK longitudinal household survey. The number of hours spent on social media was measured on a 5-point scale from \"none\" to \"7 or more hours\" at the ages of 12-13 years. Self-esteem and social connectedness (number of friends and happiness with friendships) were measured at the ages of 13-14 years. Mental health problems measured by the Strengths and Difficulties Questionnaire were assessed at the ages of 14-15 years. Covariates included demographic and household variables. Unadjusted and adjusted multilevel linear regression models were used to estimate the association between social media use and mental health. We used path analysis with structural equation modeling to investigate the mediation pathways.
In adjusted analysis, there was a nonsignificant linear trend showing that more time spent on social media was related to poorer mental health 2 years later (n=2603, β=.21, 95% CI −0.43 to 0.84; P=.52). In an unadjusted path analysis, 68% of the effect of social media use on mental health was mediated by self-esteem (indirect effect, n=2569, β=.70, 95% CI 0.15-1.30; P=.02). This effect was attenuated in the adjusted analysis, and it was found that self-esteem was no longer a significant mediator (indirect effect, n=2316, β=.24, 95% CI −0.12 to 0.66; P=.22). We did not find evidence that the association between social media and mental health was mediated by social connectedness. Similar results were found in imputed data.
There was little evidence to suggest that more time spent on social media was associated with later mental health problems in UK adolescents. This study shows the importance of longitudinal studies to examine this relationship and suggests that prevention strategies and interventions to improve mental health associated with social media use could consider the role of factors like self-esteem.

Most existing facility assessments collect data on a sample of health facilities. Sampling of health facilities may introduce bias into estimates of effective coverage generated by ecologically linking individuals to health providers based on geographic proximity or administrative catchment.
We assessed the bias introduced to effective coverage estimates produced through two ecological linking approaches (administrative unit and Euclidean distance) applied to a sample of health facilities. Our analysis linked MICS household survey data on care-seeking for child illness and childbirth care with data on service quality collected from a census of health facilities in the Savanes region of Cote d\'Ivoire. To assess the bias introduced by sampling, we drew 20 random samples of three different sample sizes from our census of health facilities. We calculated effective coverage of sick child and childbirth care using both ecological linking methods applied to each sampled facility data set. We compared the sampled effective coverage estimates to ecologically linked census-based estimates and estimates based on true source of care. We performed sensitivity analyses with simulated preferential care-seeking from higher-quality providers and randomly generated provider quality scores.
Sampling of health facilities did not significantly bias effective coverage compared to either the ecologically linked estimates derived from a census of facilities or true effective coverage estimates using the original data or simulated random quality sensitivity analysis. However, a few estimates based on sampling in a setting where individuals preferentially sought care from higher-quality providers fell outside of the estimate bounds of true effective coverage. Those cases predominantly occurred using smaller sample sizes and the Euclidean distance linking method. None of the sample-based estimates fell outside the bounds of the ecologically linked census-derived estimates.
Our analyses suggest that current health facility sampling approaches do not significantly bias estimates of effective coverage produced through ecological linking. Choice of ecological linking methods is a greater source of bias from true effective coverage estimates, although facility sampling can exacerbate this bias in certain scenarios. Careful selection of ecological linking methods is essential to minimize the potential effect of both ecological linking and sampling error.

Although cultural ecosystem services (CES) are greatly valued by diverse stakeholders, the full range of CES provided by a landscape is notoriously difficult to estimate. The resulting lack of objective norms for CES may lead to the loss of the multiple non-material factors that contribute to how a landscape is valued and experienced. This is especially true under ecological restoration, which could sharply change how people experience landscapes. Therefore, our aim in this study was to identify and analyze the CES that arise from people\'s interaction with their landscape, focusing specifically on the influences of different ecological restoration strategies. We carried out semi-structured interviews with the residents of villages in the Xilin Gol League, Inner Mongolia, China. Regarding the implementation of ecological restoration measures, the people living in typical pastoral zones would be most affected by these measures because their main livelihood (animal husbandry) depends strongly on grasslands. Our results demonstrated that human perception of the CES provided by landscapes is affected not only by the factors related to an individual\'s cultural worldview (e.g., ethnicity, age, education) but also by the utility of landscape features, which are reflected in the individual\'s landscape dependence (occupation). Our research provides a cultural perspective for aspects of local well-being in addition to ecological and economic targets. Understanding these other aspects is critical for implementing sustainable ecological restoration.

Geographic proximity is often used to link household and health provider data to estimate effective coverage of health interventions. Existing household surveys often provide displaced data on the central point within household clusters rather than household location. This may introduce error into analyses based on the distance between households and providers.
We assessed the effect of imprecise household location on quality-adjusted effective coverage of child curative services estimated by linking sick children to providers based on geographic proximity. We used data on care-seeking for child illness and health provider quality in Southern Province, Zambia. The dataset included the location of respondent households, a census of providers, and data on the exact outlets utilized by sick children included in the study. We displaced the central point of each household cluster point five times. We calculated quality-adjusted coverage by assigning each sick child to a provider\'s care based on three measures of geographic proximity (Euclidean distance, travel time, and geographic radius) from the household location, cluster point, and displaced cluster locations. We compared the estimates of quality-adjusted coverage to each other and estimates using each sick child\'s true source of care. We performed sensitivity analyses with simulated preferential care-seeking from higher-quality providers and randomly generated provider quality scores.
Fewer children were linked to their true source of care using cluster locations than household locations. Effective coverage estimates produced using undisplaced or displaced cluster points did not vary significantly from estimates produced using household location data or each sick child\'s true source of care. However, the sensitivity analyses simulating greater variability in provider quality showed bias in effective coverage estimates produced with the geographic radius and travel time method using imprecise location data in some scenarios.
Use of undisplaced or displaced cluster location reduced the proportion of children that linked to their true source of care. In settings with minimal variability in quality within provider categories, the impact on effective coverage estimates is limited. However, use of imprecise household location and choice of geographic linking method can bias estimates in areas with high variability in provider quality or preferential care-seeking.

Household surveys remain important sources of maternal and child health data, but until now, standard surveys such as Demographic and Health Surveys (DHS) have not collected information on maternity care for women who have experienced a stillbirth. Thus, nationally representative data are lacking to inform programmes to address the millions of stillbirths which occur annually.
The EN-INDEPTH population-based survey of women of reproductive age was undertaken in five Health and Demographic Surveillance System sites in Bangladesh, Ethiopia, Ghana, Guinea-Bissau and Uganda (2017-2018). All women answered a full birth history with additional questions on pregnancy losses (FBH+) or full pregnancy history (FPH). A sub-sample, including all women reporting a recent stillbirth or neonatal death, was asked additional maternity care questions. These were evaluated using descriptive measures. Associations between stillbirth and maternal socio-demographic characteristics, babies\' characteristics and maternity care use were assessed using a weighted logistic regression model for women in the FBH+ group.
A total of 15,591 women reporting a birth since 1 January 2012 answered maternity care questions. Completeness was very high (> 99%), with similar proportions of responses for both live and stillbirths. Amongst the 14,991 births in the FBH+ group, poorer wealth status, higher parity, large perceived baby size-at-birth, preterm or post-term birth, birth in a government hospital compared to other locations and vaginal birth were associated with increased risk of stillbirth after adjusting for potential confounding factors. Regarding association with reported postnatal care, women with a stillbirth were more likely to report hospital stays of > 1 day. However, women with a stillbirth were less likely to report having received a postnatal check compared to those with a live birth.
Women who had experienced stillbirth were able to respond to questions about pregnancy and birth, and we found no reason to omit questions to these women in household surveys. Our analysis identified several potentially modifiable factors associated with stillbirth, adding to the evidence-base for policy and action in low- and middle-income contexts. Including these questions in DHS-8 would lead to increased availability of population-level data to inform action to end preventable stillbirths.

Termination of pregnancy (TOP) is a common cause of maternal morbidity and mortality in low- and middle-income countries. Population-based surveys are the major data source for TOP data in LMICs but are known to have shortcomings that require improving. The EN-INDEPTH multi-country survey employed a full pregnancy history approach with roster and new questions on TOP and Menstrual Restoration. This mixed methods paper assesses the completeness of responses to questions eliciting TOP information from respondents and reports on practices, barriers, and facilitators to TOP reporting.
The EN-INDEPTH study was a population-based cross-sectional study. The Full Pregnancy History arm of the study surveyed 34,371 women of reproductive age between 2017 and 2018 in five Health and Demographic Surveillance System (HDSS) sites of the INDEPTH network: Bandim, Guinea-Bissau; Dabat, Ethiopia; IgangaMayuge, Uganda; Kintampo, Ghana; and Matlab, Bangladesh. Completeness and time spent in answering TOP questions were evaluated using simple tabulations and summary statistics. Exact binomial 95% confidence intervals were computed for TOP rates and ratios. Twenty-eight (28) focus group discussions were undertaken and analysed thematically.
Completeness of responses regarding TOP was between 90.3 and 100.0% for all question types. The new questions elicited between 2.0% (1.0-3.4), 15.5% (13.9-17.3), and 11.5% (8.8-14.7) lifetime TOP cases over the roster questions from Dabat, Ethiopia; Matlab, Bangladesh; and Kintampo, Ghana, respectively. The median response time on the roster TOP questions was below 1.3 minutes in all sites. Qualitative results revealed that TOP was frequently stigmatised and perceived as immoral, inhumane, and shameful. Hence, it was kept secret rendering it difficult and uncomfortable to report. Miscarriages were perceived to be natural, being easier to report than TOP. Interviewer techniques, which were perceived to facilitate TOP disclosure, included cultural competence, knowledge of contextually appropriate terms for TOP, adaptation to interviewee\'s individual circumstances, being non-judgmental, speaking a common language, and providing detailed informed consent.
Survey roster questions may under-represent true TOP rates, since the new questions elicited responses from women who had not disclosed TOP in the roster questions. Further research is recommended particularly into standardised training and approaches to improving interview context and techniques to facilitate TOP reporting in surveys.