Mapping diabetes burden by school-district for school-based diabetes prevention interventions in selected cities in Michigan, USA.

To decrease diabetes morbidity and mortality rates, early interventions are needed to change lifestyles that are often cemented early, making school-based interventions important. However, with limited resources and lack of within-county diabetes data, it is difficult to determine which local areas require intervention. To identify at-risk school districts, this study mapped diabetes prevalence and related deaths by school district using geographic information systems (GIS). The 2010-2014 records of diabetes-related deaths were identified for 13 cities in Michigan, USA. Diabetes prevalence was estimated using the weighted average of population by school district from the '500 Cities Project' of the Centres of Disease Control and prevention (CDC). Prevalence and mortality rates were mapped by school district and the correlation between diabetes prevalence and mortality rate analysed using the Spearman's rank correlation. Years of potential life lost (YPLL) were calculated using a 75-year endpoint. The result indicated there were geographic variations in diabetes prevalence, mortality and YPLL across Michigan. Most census tracts in the cities of Detroit, Flint and downtown Grand Rapids had higher diabetes prevalence and mortality rate with rs (628)=0.52, P<0.005. School districts with high mortality rates also had high prevalence with rs (13)=0.72, P=0.002. Flint City School District showed a higher rate of diabetes prevalence, death and YPLL than others and should thus be considered a priority for diabetes prevention interventions. Using school districts as the geographic spatial unit of analysis, we identified local variation in diabetes burden for targeting school-based diabetes prevention interventions.

Predicting coliform presence in private wells as a function of well characteristics, parcel size and leachfield soil rating.

Public water systems must be tested frequently for coliform bacteria to determine whether other pathogens may be present, yet no testing or disinfection is required for private wells. In this paper, we identify whether well age, type of well, well depth, parcel size, and soil ratings for a leachfield can predict the probability of detecting coliform bacteria in private wells using a multivariate logistic regression model. Samples from 1163 wells were analyzed for the presence of coliform bacteria between October 2017 and October 2019 across Gaston County, North Carolina, USA. The maximum well age was 30 years, and bored wells (median age = 24 years) were older than drilled wells (median age = 19 years). Bored wells were shallower (mean depth = 18 m) compared to drilled wells (mean depth = 79 m). We found coliform bacteria in 329 samples, including 290 of 1091 drilled wells and 39 of 72 bored wells. The model results showed bored wells were 4.76 times more likely to contain bacteria compared to drilled wells. We found that the likelihood of coliform bacteria significantly increased with well age, suggesting that those constructed before well standards were enforced in 1989 may be at a higher risk. We found no significant association between poorly rated soils for a leachfield, well depth, parcel size and the likelihood of having coliform in wells. These findings can be leveraged to determine areas of concern to encourage well users to take action to reduce their risk of drinking possible pathogens in well water.

Using GIS and death records to inform statewide school-based diabetes prevention interventions in Michigan.

Background: One of modifiable risk factors of diabetes is unhealthy diet which is related to obesity. Individuals with childhood obesity are at higher risk of adulthood obesity. School-based diabetes prevention programs are important to reduce childhood obesity. When resources are limited, evidence-based priority need to be undertaken. However, data related to childhood obesity was not widely available, the study used diabetes-related death records as the proxy of diabetes burden. This study aimed to map and identify geographic variation of diabetes-related mortality rate by school district level in Michigan to be used for policy-relevant information. Design and Methods: This study used death records in Michigan. Diabetes-related mortality rate and years potential life lost (YPLL) was calculated at the school district level. Spatial autocorrelation local Moran's I and geographically weighted regression were used to evaluate spatial pattern of age-adjusted diabetes-related mortality rate by school districts. Results: The age-adjusted diabetes-related mortality rate ranged from 17.0 (95% CI, 8.6-25.5) to 171.3 (95% CI, 135.9-206.7) deaths per 100,000 population. The YPLL per person ranged from 0 to 19.3 years (95% CI, 15.5-23.1). High rates of diabetes-related mortality rate and YPLL clustered in East central and Southeastern region of Lower Peninsula Michigan including Flint, Kearsley, Beecher, Westwood Heights, Detroit, Ecorse, River Rouge, Taylor, Allen Park and Lincoln Consolidated school districts. Conclusions: There was variation in diabetes burden examined by diabetes-related mortality rate and YPLL at the school district level within Michigan State. The high cluster can be prioritized for the intervention programs.

Residential mobility impacts relative risk estimates of space-time clusters of chlamydia in Kalamazoo County, Michigan.

We determine the impact of residential mobility in the prevalence and transmission dynamics of sexually transmitted infections. We illustrate our approach on reported chlamydia infections obtained from the Michigan Disease Surveillance System for Kalamazoo County, USA, from 2006 to 2014. We develop two scenarios, one with fixed residential addresses and one considering residential mobility. We then compare the resulting space-time clusters and relative risk (RR) of infection. The space-time scan statistics showed increased RR in an area with previously low risk of sexually transmitted infections. In addition, even though the spatial extent of the three clusters identified did not change significantly at the scale we conducted our analysis at, the temporal extent (duration) did exhibit significant changes and could be considered for unique interventions. The results indicate that residential mobility has some dependency on the prevalence and transmission dynamics of sexually transmitted infections to new areas. We suggest that strategies adopted to reduce the burden of sexually transmitted infections take into consideration the relatively high residential mobility of at-risk populations to reduce spreading the infections to new areas.

Assessing the association of diabetes self-management education centers with age-adjusted diabetes rates across U.S.: Aspatial cluster analysis approach.

The purpose of this study is to identify regions with diabetes health-service shortage. American Diabetes Association (ADA)-accredited diabetes self-management education (DSME) is recommended for all those with diabetes. In this study, we focus on demographic patterns and geographic regionalization of the disease by including accessibility and availability of diabetes education resources as a critical component in understanding and confronting differences in diabetes prevalence, as well as addressing regional or sub-regional differences in awareness, treatment and control. We conducted an ecological county-level study utilizing publicly available secondary data on 3,109 counties in the continental U.S. We used a Bayesian spatial cluster model that enabled spatial heterogeneities across the continental U.S. to be addressed. We used the American Diabetes Association (ADA) website to identify 2012 DSME locations and national 2010 county-level diabetes rates estimated by the Centers for Disease Control and Prevention and identified regions with low DSME program availability relative to their diabetes rates and population density. Only 39.8% of the U.S. counties had at least one ADA-accredited DSME program location. Based on our 95% credible intervals, age-adjusted diabetes rates and DSME program locations were associated in only seven out of thirty five identified clusters. Out of these seven, only two clusters had a positive association. We identified clusters that were above the 75th percentile of average diabetes rates, but below the 25th percentile of average DSME location counts and found that these clusters were all located in the Southeast portion of the country. Overall, there was a lack of relationship between diabetes rates and DSME center locations in the U.S., suggesting resources could be more efficiently placed according to need. Clusters that were high in diabetes rates and low in DSME placements, all in the southeast, should particularly be considered for additional DSME programming.

Modelling individual vulnerability to sexually transmitted infections to optimise intervention strategies: analysis of surveillance data from Kalamazoo County, Michigan, USA.

OBJECTIVE: We modelled individual vulnerability to STI using personal history of infection and neighbourhood characteristics. METHODS: Retrospective chlamydia and gonorrhoea data of reported confirmed cases from Kalamazoo County, Michigan for 2012 through 2014 were analysed. Unique IDs were generated from the surveillance data in collaboration with local health officials to track the individual STI histories. We then examine the concept that individuals with similar STI histories form a 'peer' group. These peer group include: (1) individuals with a single chlamydia; (2) individuals with single gonorrhoea; (3) individuals with repeated cases of one type of STI and (4) individuals that were diagnosed with both infections during the study period. Using Kernel density estimation, we generated densities for each peer group and assigned the intensity of the infection to the location of the individual. Finally, the individual vulnerability was characterised through ordinary least square regression (OLS) using demographics and socioeconomic variables. RESULTS: In an OLS regression adjusted for frequency of infection, individual vulnerability to STI was only consistently significant for race and neighbourhood-level socioeconomic status (SES) in all the models under consideration. In addition, we identified six areas in three townships in Kalamazoo County that could be considered for unique interventions based on overlap patterns among peer groups. CONCLUSIONS: The results provide evidence that individual vulnerability to STI has some dependency on individual contextual (race) and exogenous factors at the neighbourhood level such as SES, regardless of that individual's personal history of infection. We suggest place-based intervention strategies be adopted for planning STI interventions instead of current universal screening of at-risk populations.

Prevalence and diversity of avian Haemosporida infecting songbirds in southwest Michigan.

Avian blood parasites from the genera Plasmodium, Haemoproteus, and Leucocytozoon (Haemosporida) affect hosts in numerous ways. They influence species interactions, host behavior, reproductive success, and cause pathology and mortality in birds. The Great Lakes region of North America has extensive aquatic and wetland habitat and supports a diverse vector community. Here we describe the community of bird-infecting Haemosporida in southwest Michigan and their host associations by measuring parasite prevalence, diversity, and host breadth across a diverse community of avian hosts. Over 700 songbirds of 55 species were screened for Haemosporida infection across southwest Michigan, including 11 species that were targeted for larger sample sizes. In total, 71 parasite lineages infected over 40% of birds. Of these, 42 were novel, yet richness estimates suggest that approximately half of the actual parasite diversity in the host community was observed despite intensive sampling of multiple host species. Parasite prevalence varied among parasite genera (7-24%) and target host species (0-85%), and parasite diversity was consistently high across most target species. Host breadth varied widely across the most prevalent parasite lineages, and we detected around 60% of host species richness for these parasite lineages. We report many new lineages and novel host-parasite associations, but substantial parasite diversity remains undiscovered in the Midwest.

Decomposing an urban soundscape to reveal patterns and drivers of variation in anthropogenic noise.

Continuous and intermittent noise may have different effects on humans and wildlife, therefore distinguishing temporal patterns of noise and their drivers is important for policy regarding both public health and wildlife management. We visualized patterns and explored land-use drivers of continuous and high-amplitude intermittent sound pressure levels (SPLs) on an urban campus in Michigan, U.S.A. To visualize patterns of SPLs, we introduce decibel duration curves (DDCs), which show the cumulative frequency distribution of SPLs and aid in the interpretation of statistical SPLs (Ln values) that reflect continuous versus intermittent sounds. DDCs and Ln values reveal that our 24 recording locations varied in the intensity of both continuous and intermittent noise, with intermittent high-amplitude sound events in particular contributing to variability in SPLs over the study site. Time of day influenced both continuous and intermittent SPLs, as locations relatively close to manmade structures (buildings, roads and parking lots) experienced higher SPLs as the day progressed. Continuous SPLs increased with decreasing distance to manmade structures, whereas intermittent SPLs increased with decreasing distance to roads and increasing distance to buildings. Thus, different land-use factors influenced patterns of continuous and intermittent noise, which suggests that different policy and strategies may be needed to ameliorate their effects on the public and wildlife.

A test of the circumvention-of-limits hypothesis in scientific problem solving: the case of geological bedrock mapping.

Sources of individual differences in scientific problem solving were investigated. Participants representing a wide range of experience in geology completed tests of visuospatial ability and geological knowledge, and performed a geological bedrock mapping task, in which they attempted to infer the geological structure of an area in the Tobacco Root Mountains of Montana. A Visuospatial Ability × Geological Knowledge interaction was found, such that visuospatial ability positively predicted mapping performance at low, but not high, levels of geological knowledge. This finding suggests that high levels of domain knowledge may sometimes enable circumvention of performance limitations associated with cognitive abilities.