OBJECTIVEWe previously described a cross-sectional association between serum uric acid and reduced glomerular filtration rate (GFR) in nonproteinuric patients with type 1 diabetes. Here, we prospectively investigated whether baseline uric acid impacts the risk of early progressive renal function loss (early GFR loss) in these patients.RESEARCH DESIGN AND METHODSPatients with elevated urinary albumin excretion (n = 355) were followed for 4–6 years for changes in urinary albumin excretion and GFR. The changes were estimated by multiple determinations of albumin-to-creatinine ratios (ACRs) and serum cystatin C (GFRcystatin).RESULTSAt baseline, the medians (25th–75th percentiles) for uric acid, ACR, and GFRcystatin values were 4.6 mg/dl (3.8–5.4), 26.2 mg/g (15.1–56.0), and 129 ml/min per 1.73 m2 (111–145), respectively. During the 6-year follow-up, significant association (P < 0.0002) was observed between serum uric acid and development of early GFR loss, defined as GFRcystatin decline exceeding 3.3% per year. In baseline uric acid concentration categories (in mg/dl: <3.0, 3.0–3.9, 4.0–4.9, 5.0–5.9, and ≥6), the risk of early GFR loss increased linearly (9, 13, 20, 29, and 36%, respectively). This linear increase corresponds to odds ratio 1.4 (95% CI 1.1–1.8) per 1 mg/dl increase of uric acid. The progression and regression of urinary albumin excretion were not associated with uric acid.CONCLUSIONSWe found a clear dose-response relation between serum uric acid and risk of early GFR loss in patients with type 1 diabetes. Clinical trials are warranted to determine whether uric acid–lowering drugs can halt renal function decline before it becomes clinically significant.

BackgroundMapping spatial distributions of disease occurrence and risk can serve as a useful tool for identifying exposures of public health concern. Disease registry data are often mapped by town or county of diagnosis and contain limited data on covariates. These maps often possess poor spatial resolution, the potential for spatial confounding, and the inability to consider latency. Population-based case-control studies can provide detailed information on residential history and covariates.ResultsGeneralized additive models (GAMs) provide a useful framework for mapping point-based epidemiologic data. Smoothing on location while controlling for covariates produces adjusted maps. We generate maps of odds ratios using the entire study area as a reference. We smooth using a locally weighted regression smoother (loess), a method that combines the advantages of nearest neighbor and kernel methods. We choose an optimal degree of smoothing by minimizing Akaike's Information Criterion. We use a deviance-based test to assess the overall importance of location in the model and pointwise permutation tests to locate regions of significantly increased or decreased risk. The method is illustrated with synthetic data and data from a population-based case-control study, using S-Plus and ArcView software.ConclusionOur goal is to develop practical methods for mapping population-based case-control and cohort studies. The method described here performs well for our synthetic data, reproducing important features of the data and adequately controlling the covariate. When applied to the population-based case-control data set, the method suggests spatial confounding and identifies statistically significant areas of increased and decreased odds ratios.

The relationship between community drinking water quality and the occurrence of late adverse pregnancy outcomes was investigated by conducting a case-control study among women who delivered infants during August 1977 through March 1980 at Brigham and Women's Hospital in Massachusetts. The water quality indices were compared among 1,039 congenital anomaly cases, 77 stillbirth cases, 55 neonatal death cases, and 1,177 controls. Trace element levels were gathered from routine analyses of public water supplies from the communities in which the women resided during pregnancy. It was observed that, after adjustment for confounding, the frequency of stillbirths was increased for women exposed to chlorinated surface water (OR 2.6 95% CI 0.9-7.5) and for women exposed to detectable lead levels (OR 2.1; 95% CI 0.6-7.2); the frequency of cardiovascular defects was increased relative to detectable lead levels (OR 2.2, 95% CI 0.9-5.7); and the frequency of central nervous system defects was increased relative to the highest tertile of potassium (OR 6.3, 95% CI 1.1-37.3). The frequency of ear, face, and neck anomalies was increased in relation to detectable silver levels (OR 3.3, 95% CI 0.9-12.2), but the frequency decreased relative to high potassium levels (OR 0.2, 95% CI 0.1-0.7). The frequency of neonatal deaths was decreased relative to detectable fluoride levels (OR 0.4, 95% CI 0.2-1.0), and the frequency of musculoskeletal defects was decreased relative to detectable chromium levels (OR 0.4, 95% CI 0.2-1.0). The majority of these associations were not stable statistically. Further research is needed to corroborate these findings.

In 1998 we published the results of a study suggesting an association between breast cancer and perchloroethylene (PCE; also called tetrachloroethylene) exposure from public drinking water. The present case-control study was undertaken to evaluate this association further. The cases were composed of female residents of eight towns in the Cape Cod region of Massachusetts who had been diagnosed with breast cancer from 1987 through 1993 (n = 672). Controls were composed of demographically similar women from the same towns (n = 616). Women were exposed to PCE when it leached from the vinyl lining of water distribution pipes from the late 1960s through the early 1980s. A relative delivered dose of PCE that entered a home was estimated using an algorithm that took into account residential history, water flow, and pipe characteristics. Small to moderate elevations in risk were seen among women whose exposure levels were above the 75th and 90th percentiles when 0-15 years of latency were considered (adjusted odds ratios, 1.5-1.9 for > 75th percentile, 1.3-2.8 for > 90th percentile). When data from the present and prior studies were combined, small to moderate increases in risk were also seen among women whose exposure levels were above the 75th and 90th percentiles when 0-15 years of latency were considered (adjusted odds ratios, 1.6-1.9 for > 75th percentile, 1.3-1.9 for > 90th percentile). The results of the present study confirm those of the previous one and suggest that women with the highest PCE exposure levels have a small to moderate increased risk of breast cancer.