Sea turtle products (e.g., meat, adipose tissue, organs, blood, eggs) are common food items for many communities worldwide, despite national regulations in some countries prohibiting such consumption.However, there may be hazards associated with this consumption due to the presence of bacteria, parasites, biotoxins, and environmental contaminants. Reported health effects of consuming sea turtles infected with zoonotic pathogens include diarrhea, vomiting, and extreme dehydration, which occasionally have resulted in hospitalization and death. Levels of heavy metals and organochlorine compounds measured in sea turtle edible tissues exceed international food safety standards and could result in toxic effects including neurotoxicity, kidney disease, liver cancer, and developmental effects in fetuses and children. The health data presented in this review provide information to health care providers and the public concerning the potential hazards associated with sea turtle consumption. Based on past mortality statistics from turtle poisonings, nursing mothers and children should be particularly discouraged from consuming all sea turtle products. We recommend that individuals choose seafood items lower in the food chain that may have a lower contaminant load. Dissemination of this information via a public health campaign may simultaneously improve public health and enhance sea turtle conservation by reducing human consumption of these threatened and endangered species.
BackgroundThe history of Chagas disease control in Peru and many other nations is marked by scattered and poorly documented vector control campaigns. The complexities of human migration and sporadic control campaigns complicate evaluation of the burden of Chagas disease and dynamics of Trypanosoma cruzi transmission.Methodology/Principal FindingsWe conducted a cross-sectional serological and entomological study to evaluate temporal and spatial patterns of T. cruzi transmission in a peri-rural region of La Joya, Peru. We use a multivariate catalytic model and Bayesian methods to estimate incidence of infection over time and thereby elucidate the complex history of transmission in the area. Of 1,333 study participants, 101 (7.6%; 95% CI: 6.2–9.0%) were confirmed T. cruzi seropositive. Spatial clustering of parasitic infection was found in vector insects, but not in human cases. Expanded catalytic models suggest that transmission was interrupted in the study area in 1996 (95% credible interval: 1991–2000), with a resultant decline in the average annual incidence of infection from 0.9% (95% credible interval: 0.6–1.3%) to 0.1% (95% credible interval: 0.005–0.3%). Through a search of archival newspaper reports, we uncovered documentation of a 1995 vector control campaign, and thereby independently validated the model estimates.Conclusions/SignificanceHigh levels of T. cruzi transmission had been ongoing in peri-rural La Joya prior to interruption of parasite transmission through a little-documented vector control campaign in 1995. Despite the efficacy of the 1995 control campaign, T. cruzi was rapidly reemerging in vector populations in La Joya, emphasizing the need for continuing surveillance and control at the rural-urban interface.
Standard Definitions is a work in progress; this is the eighth major edition. The American Association for Public Opinion Research plans to continue updating it, adding comparable definitions for other modes of data collection and making other refinements. AAPOR also is working with other organizations to further the widespread adoption and utilization of Standard Definitions. AAPOR is seeking the cooperation of companies that provide computer-assisted telephone interviewing (CATI) software. Some of these companies already have agreed to incorporate the definitions and formula into their software reports. AAPOR also is asking academic journals to use AAPOR standards in their evaluation and publication of articles; several, including Public Opinion Quarterly and the International Journal of Public Opinion Research, already have agreed to do so.The first edition (1998) was based on the work of a committee headed by Tom W. Smith. Other AAPOR members who served on the committee include
One challenge to achieving Millennium Development Goals was inequitable access to quality health services. In order to achieve the Sustainable Development Goals, interventions need to reach underserved populations. Analyzing health indicators in small geographic units aids the identification of hotspots where coverage lags behind neighboring areas. The purpose of these analyses is to identify areas of low coverage or high need in order to inform effective resource allocation to reduce child health inequity between and within countries. Using data from The Demographic and Health Survey Program surveys conducted in 27 selected African countries between 2010 and 2014, we computed estimates for six child health indicators for subnational regions. We calculated Global Moran’s I statistics and used Local Indicator of Spatial Association analysis to produce a spatial layer showing spatial associations. We created maps to visualize sub-national autocorrelation and spatial clusters. The Global Moran’s I statistic was positive for each indicator (range: 0.41 to 0.68), and statistically significant (p <0.05), suggesting spatial autocorrelation across national borders, and highlighting the need to examine health indicators both across countries and within them. Patterns of substantial differences among contiguous subareas were apparent; the average intra-country difference for each indicator exceeded 20 percentage points. Clusters of cross-border associations were also apparent, facilitating the identification of hotspots and informing the allocation of resources to reduce child health inequity between and within countries. This study exposes differences in health indicators in contiguous geographic areas, indicating that specific regional and subnational, in addition to national, strategies to improve health and reduce health inequalities are warranted.
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