Sumeet Patil and colleagues conduct a cluster randomized controlled trial to measure the effect of India's Total Sanitation Campaign in Madhya Pradesh on the availability of individual household latrines, defecation behaviors, and child health. Please see later in the article for the Editors' Summary

Risk communication and consumer education to promote safer handling of food can be the best way of managing the risk of foodborne illness at the consumer end of the food chain. Thus, an understanding of the overall status of food handling knowledge and practices is needed. Although traditional qualitative reviews can be used for combining information from several studies on specific food handling behaviors, a structured approach of meta-analysis can be more advantageous in a holistic assessment. We combined findings from 20 studies using meta-analysis methods to estimate percentages of consumers engaging in risky behaviors, such as consumption of raw food, poor hygiene, and cross-contamination, separated by various demographic categories. We estimated standard errors to reflect sampling error and between-study random variation. Then we evaluated the statistical significance of differences in behaviors across demographic categories and across behavioral measures. There were considerable differences in behaviors across demographic categories, possibly because of socioeconomic and cultural differences. For example, compared with women, men reported greater consumption of raw or undercooked foods, poorer hygiene, poorer practices to prevent cross-contamination, and less safe defrosting practices. Mid-age adults consumed more raw food (except milk) than did young adults and seniors. High-income individuals reported greater consumption of raw foods, less knowledge of hygiene, and poorer cross-contamination practices. The highest raw ground beef and egg consumption and the poorest hygiene and cross-contamination practices were found in the U.S. Mountain region. Meta-analysis was useful for identifying important data gaps and demographic groups with risky behaviors, and this information can be used to prioritize further research.

Objective To determine the effectiveness of a sanitation campaign that combines "shaming" (i.e. emotional motivators) with subsidies for poor households in rural Orissa, an Indian state with a disproportionately high share of India's child mortality. Methods Using a cluster-randomized design, we selected 20 treatment and 20 control villages in the coastal district of Bhadrak, rural Orissa, for a total sample of 1050 households. We collected sanitation and health data before and after a community-led sanitation project, and we used a difference-in-difference estimator to determine the extent to which the campaign influenced the number of households building and using a latrine. Findings Latrine ownership did not increase in control villages, but in treatment villages it rose from 6% to 32% in the overall sample, from 5% to 36% in households below the poverty line (eligible for a government subsidy) and from 7% to 26% in households above the poverty line (not eligible for a government subsidy). Conclusion Subsidies can overcome serious budget constraints but are not necessary to spur action, for shaming can be very effective by harnessing the power of social pressure and peer monitoring. Through a combination of shaming and subsidies, social marketing can improve sanitation worldwide.Une traduction en français de ce résumé figure à la fin de l'article. Al final del artículo se facilita una traducción al español. ‫املقالة.‬ ‫لهذه‬ ‫الكامل‬ ‫النص‬ ‫نهاية‬ ‫يف‬ ‫الخالصة‬ ‫لهذه‬ ‫العربية‬ ‫الرتجمة‬

Identification and qualitative comparison of sensitivity analysis methods that have been used across various disciplines, and that merit consideration for application to food-safety risk assessment models, are presented in this article. Sensitivity analysis can help in identifying critical control points, prioritizing additional data collection or research, and verifying and validating a model. Ten sensitivity analysis methods, including four mathematical methods, five statistical methods, and one graphical method, are identified. The selected methods are compared on the basis of their applicability to different types of models, computational issues such as initial data requirement and complexity of their application, representation of the sensitivity, and the specific uses of these methods. Applications of these methods are illustrated with examples from various fields. No one method is clearly best for food-safety risk models. In general, use of two or more methods, preferably with dissimilar theoretical foundations, may be needed to increase confidence in the ranking of key inputs.

No. DP0987011. The opinions expressed in this paper are those of the authors alone and do not necessarily represent the opinions of the organizations where they work or of the funders. The authors have no material or financial interests in the results or opinions expressed in the paper. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

Despite strong policy and program commitment, essential maternal nutrition services are not reaching enough women in many countries. This paper examined multifactorial determinants (personal, family, community, and health services) associated with maternal nutrition practices in Uttar Pradesh, India. Data were from a household survey of pregnant (n = 667) and recently delivered women (n = 1,835). Multivariable regression analyses were conducted to examine the determinants of four outcomes: consumption of diverse diets, consumption of iron folic acid (IFA) and calcium tablets, and weight monitoring during pregnancy. Population attributable risk analysis was used to estimate how much the outcomes can be improved under optimal program implementation. During pregnancy, women consumed 28 IFA and 8 calcium tablets, 18% consumed diverse diet, and 17% were weighed ≥3 times. Nutrition knowledge was associated with consumption of diverse diet (odds ratio [OR] = 2.2 times), IFA (2.3 times), calcium (11.7 times), and weight monitoring (1.3 times). Beliefs and self‐efficacy were associated with IFA (OR = 2.0) and calcium consumption (OR = 4.6). Family support and adequate health services were also associated with better nutrition practices. Under optimal program implementation, we estimate that 51% of women would have adequate diet diversity, an average consumption of 98 IFA, and 106 calcium tablets, and women would be weighed 4.9 times during pregnancy. Strengthening existing program operations and increasing demand for services has the potential to result in large improvements in maternal nutrition practices from current baseline levels but may not be sufficient to meet World Health Organization‐recommended levels without creating an enabling environment including improvements in education and income levels to support behaviour change.

also provided helpful discussion.

Sensitivity analysis (SA) methods are a valuable tool for identifying critical control points (CCPs), which is one of the important steps in the hazard analysis and CCP approach that is used to ensure safe food. There are many SA methods used across various disciplines. Furthermore, food safety process risk models pose challenges because they often are highly nonlinear, contain thresholds, and have discrete inputs. Therefore, it is useful to compare and evaluate SA methods based upon applications to an example food safety risk model. Ten SA methods were applied to a draft Vibrio parahaemolyticus (Vp) risk assessment model developed by the Food and Drug Administration. The model was modified so that all inputs were independent. Rankings of key inputs from different methods were compared. Inputs such as water temperature, number of oysters per meal, and the distributional assumption for the unrefrigerated time were the most important inputs, whereas time on water, fraction of pathogenic Vp, and the distributional assumption for the weight of oysters were the least important inputs. Most of the methods gave a similar ranking of key inputs even though the methods differed in terms of being graphical, mathematical, or statistical, accounting for individual effects or joint effect of inputs, and being model dependent or model independent. A key recommendation is that methods be further compared by application on different and more complex food safety models. Model independent methods, such as ANOVA, mutual information index, and scatter plots, are expected to be more robust than others evaluated.