ObjectivesIncreasing evidence suggests that water, sanitation and hygiene (WASH) practices affect linear growth in early childhood. We determined the association between household access to water, sanitation and personal hygiene practices with stunting among children aged 0–23 months in rural India.SettingIndia.ParticipantsA total of 10 364, 34 639 and 1282 under-2s who participated in the 2005–2006 National Family Health Survey (NFHS-3), the 2011 Hunger and Malnutrition Survey (HUNGaMA) and the 2012 Comprehensive Nutrition Survey in Maharashtra (CNSM), respectively, were included in the analysis.Primary outcome measuresThe association between WASH indicators and child stunting was assessed using logistic regression models.ResultsThe prevalence of stunting ranged from 25% to 50% across the three studies. Compared with open defecation, household access to toilet facility was associated with a 16–39% reduced odds of stunting among children aged 0–23 months, after adjusting for all potential confounders (NHFS-3 (OR=0.84, 95% CI 0.71 to 0.99); HUNGaMA (OR=0.84, 95% CI 0.78 to 0.91); CNSM (OR=0.61, 95% CI 0.44 to 0.85)). Household access to improved water supply or piped water was not in itself associated with stunting. The caregiver's self-reported practices of washing hands with soap before meals (OR=0.85, 95% CI 0.76 to 0.94) or after defecation (OR=0.86, 95% CI 0.80 to 0.93) were inversely associated with child stunting. However, the inverse association between reported personal hygiene practices and stunting was stronger among households with access to toilet facility or piped water (all interaction terms, p<0.05).ConclusionsImproved conditions of sanitation and hygiene practices are associated with reduced prevalence of stunting in rural India. Policies and programming aiming to address child stunting should encompass WASH interventions, thus shifting the emphasis from nutrition-specific to nutrition-sensitive programming. Future randomised trials are warranted to validate the causal association.

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Introduction: Yellow fever (YF) is a vector-borne disease transmitted to humans by infected Aedes mosquitoes, while hepatitis E virus (HEV) is a waterborne disease that is transmitted through the fecal-oral route. Both diseases have very close clinical presentation, namely fever, jaundice, malaise, and dark urine; they differ in severity and outcome. Methodology: In this cross-sectional, laboratory-based study, an attempt was made to measure the correlation of concomitant YF and HEV infection in Darfur States during the previous YF outbreak in 2012. Results: Results found concomitant outbreaks of YF and HEV at the same time with very weak statistical correlation between the two infections during the outbreak period, with Cramer's V correlation 0.05 and insignificant p value of 0.86. Conclusions: This correlation indicates that clinicians and care providers in tropical areas have to deal with clinical case definitions used for disease surveillance very carefully since prevalence of HEV infection is relatively common and this increases the possibility of misclassification and missing YF cases, particularly initial index cases, in a season or outbreak.

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Recognizing that health outcomes are influenced by and occur within multiple social and physical contexts, researchers have used multilevel modeling techniques for decades to analyze hierarchical or nested data. Cross-Classified Multilevel Models (CCMM) are a statistical technique proposed in the 1990s that extend standard multilevel modeling and enable the simultaneous analysis of non-nested multilevel data. Though use of CCMM in empirical health studies has become increasingly popular, there has not yet been a review summarizing how CCMM are used in the health literature. To address this gap, we performed a scoping review of empirical health studies using CCMM to: (a) evaluate the extent to which this statistical approach has been adopted; (b) assess the rationale and procedures for using CCMM; and (c) provide concrete recommendations for the future use of CCMM. We identified 118 CCMM papers published in English-language literature between 1994 and 2018. Our results reveal a steady growth in empirical health studies using CCMM to address a wide variety of health outcomes in clustered non-hierarchical data. Health researchers use CCMM primarily for five reasons: (1) to statistically account for non-independence in clustered data structures; out of substantive interest in the variance explained by (2) concurrent contexts, (3) contexts over time, and (4) age-period-cohort effects; and (5) to apply CCMM alongside other techniques within a joint model. We conclude by proposing a set of recommendations for use of CCMM with the aim of improved clarity and standardization of reporting in future research using this statistical approach.

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The treatment of depression in the elderly population needs a thorough and careful work‐up and an aggressive therapeutic approach. Any treatment initiative in this population often becomes difficult because of accompanying physical illness, concomitant medication, possible degenerative changes in central nervous system and age‐related altered metabolic status. Despite unevenness in research findings, pharmacological treatment remains the mainstay of management of depression among elderly people. Currently available antidepressants, although effective, are problematic because of the increased vulnerability of the elderly to side effects. Recent research efforts to improve the efficacy and safety of drug treatment of depression resulted in development of reversible and selective monoamine oxidase inhibitors of the isoenzyme A (RIMA), with antidepressant efficacy comparable to tricyclic antidepressants and newer generation antidepressants. RIMAs include moclobemide, brofaromine, toloxatone and cimoxatone. Moclobemide is the most investigated available RIMA for therapeutic use at present. Its absorption and disposition in elderly individuals do not differ significantly from those in young healthy volunteers and depressed patients. The results of present clinical studies show that, in elderly depressed patients, moclobemide is at least as effective as other antidepressants. Its particular advantage is, however, that it is as well tolerated in elderly people as in younger people. There are only few significant adverse events, and they are generally less frequent and less severe than those with TCAs. An additional attribute of moclobemide seems also to be its beneficial effect on cognitive functions.

This article examines how migration impacts power dynamics and gender norms for women left behind living in rural Southern Punjab, Pakistan, a site where patriarchal customs and religion are interwoven to confine women’s mobility and agency. Based on qualitative interviews and focus groups with women left behind from 2015 through 2018, this article explores how local rural-to-urban male migration patterns impact the decision-making powers of women who are left behind and must make sense of the family structure and gender dynamics in their homes after their husbands’ exit. This study finds that in the absence of her migrant husband, a woman left behind is still subject to patriarchal norms and surveillance by the remaining in-laws, including other women. Citing specific examples from the field, I explain why women left behind remain close to the very families that confine and monitor their movement, and why, in some cases, women left behind turn a blind eye toward their husband’s second or third marriage. Through an examination of behind-the-scenes negotiations that women left behind make, I argue that women maintain for themselves at surface level the gendered expectations that patriarchy sets for them, but given the opportunity, they can negotiate and bargain their positionality in subtle ways without disrupting the status quo that could otherwise jeopardize their physical safety and social reputation (honor).