Recent research suggests that social networks may present an avenue for intervention against obesity. By using a simulation model in which artificial individuals were nested in a social network, we assessed whether interventions targeting highly networked individuals could help reduce population obesity. We compared the effects of targeting antiobesity interventions at the most connected individuals in a network with those targeting individuals at random. We tested 2 interventions, the first "preventing" obesity among 10% of the population at simulation outset and the second "treating" obesity among 10% of the obese population yearly, each in 2 separate simulations. One simulation featured a literature-based parameter for the network spread of obesity, and the other featured an artificially high parameter. Interventions that targeted highly networked individuals did not outperform at-random interventions in simulations featuring the literature-based parameter. However, in simulations featuring the artificially high parameter, the targeted prevention intervention outperformed the at-random intervention, whereas the treatment intervention implemented at random outperformed the targeted treatment intervention. Results were qualitatively similar across network topologies and intervention scales. Although descriptive studies suggest that social networks influence the spread of obesity, policies targeting well-connected individuals in social networks may not improve obesity reduction. We highlight and discuss the potential applications of counterfactual simulations in epidemiology.

The selection of controls is an important methodological consideration for case-control studies. Neighborhood-matched control selection is particularly crucial for studies of vector-borne disease, such as Lyme disease, for which risk is intrinsically linked to geographical location. The matching of case-control pairs on neighborhood can help control for variation in ecological risk factors that are tied to geographical location, like vector and host habitat in the peridomestic environment. Random-digit dialing has been used to find neighborhood controls by using the area code and exchange of the case to generate lists of potential control households. An alternative to random-digit dialing is the purchase of residential telephone numbers from a commercial marketing database. This report describes the utility of the InfoUSA.com (InfoGroup, Papillion, Nebraska) commercial marketing database for neighborhood control recruitment in a Lyme disease case-control study in Connecticut during 2005-2007.

Body mass index (BMI) (calculated as weight (kg)/height (m)(2)) and height are linked to the pathogenesis of low back pain, but evidence-based confirmation is lacking. We examined the prevalence of low back pain in adolescents and its association with BMI and height. Disability clauses (official military limitations related to a person's health status) indicating low back pain severity were divided according to symptoms of low back pain alone and symptoms of low back pain with objective corroborating findings. All 829,791 males and females undergoing mandatory premilitary recruitment examinations since 1998 were included. Logistic regression models assessed the relationships of BMI and height with low back pain. Prevalence of low back pain was 0.2% for both males and females with objective findings and 5.2% for males and 2.7% for females without objective findings. Higher BMI was significantly associated with low back pain in males (for overweight, odds ratio = 1.097, P < 0.001; for obese, odds ratio = 1.163, P < 0.001) and in females (for overweight, odds ratio = 1.174, P < 0.001; for obese, odds ratio = 1.211, P < 0.001). Height was associated with increased risk of low back pain in both genders. Odds ratios for low back pain in the tallest group compared with the shortest group were 1.438 (P < 0.001) for males and 1.224 (P < 0.001) for females. Low back pain with or without objective findings was associated with overweight and obesity as well as with height.

In this prospective cohort study, based on 1,505 mother-infant pairs in rural Bangladesh, we evaluated the associations between early-life exposure to arsenic, cadmium, and lead, assessed via concentrations in maternal and child urine, and children's weights and heights up to age 5 years, during the period 2001-2009. Concurrent and prenatal exposures were evaluated using linear regression analysis, while longitudinal exposure was assessed using mixed-effects linear regression. An inverse association was found between children's weight and height, age-adjusted z scores, and growth velocity at age 5 years and concurrent exposure to cadmium and arsenic. In the longitudinal analysis, multivariable-adjusted attributable differences in children's weight at age 5 years were -0.33 kg (95% confidence interval (CI): -0.60, -0.06) for high (≥95th percentile) arsenic exposure and -0.57 kg (95% CI: -0.88, -0.26) for high cadmium exposure, in comparison with children with the lowest exposure (≤5th percentile). Multivariable-adjusted attributable differences in height were -0.50 cm (95% CI: -1.20, 0.21) for high arsenic exposure and -1.6 cm (95% CI: -2.4, -0.77) for high cadmium exposure. The associations were apparent primarily among girls. The negative effects on children's growth at age 5 years attributable to arsenic and cadmium were of similar magnitude to the difference between girls and boys in terms of weight (-0.67 kg, 95% CI: -0.82, -0.53) and height (-1.3 cm, 95% CI: -1.7, -0.89).

Reduction of dietary sodium intake has been identified as a priority to reduce the worldwide burden of hypertension and cardiovascular disease. Dietary sodium intake is most precisely ascertained by using timed urine collection. Casual urine sodium measurements are relatively easy to perform, but their relationship to timed urine sodium measurements is unclear. In this issue of the Journal, Brown et al. (Am J Epidemiol. 2013;000(00):000-000) report the development and validation of equations to estimate 24-hour urine sodium excretion from casual urine samples. Their study included a large number of participants on 2 continents, a well-collected gold standard, separate discovery and validation samples, and relevant covariates. The resulting equations represent the best available methods to estimate dietary sodium intake from casual urine samples. However, the study is limited by evidence of a suboptimal model fit, restriction to people 20-59 years of age in North America and Europe, and exclusion and adjustment that further limit external validity. In addition, individual-level correlations of estimated and measured 24-hour urine sodium excretion were modest. Properly applied, the results will facilitate tracking of dietary sodium intake within populations over time and identification of communities for which dietary sodium restriction is most likely to be beneficial. Further work is needed to extend estimation to additional populations and improve individual-level assessment.

Obesity is an established risk factor for endometrial cancer, but this association is not well understood for subtypes of endometrial cancer. We evaluated the association of recent and adult-life obesity with subtypes of endometrial cancer based on microsatellite status (microsatellite-stable (MSS) vs. microsatellite-instable (MSI)) and histology (type I vs. type II). Analyses were based on a population-based case-control study (524 cases and 1,032 controls) conducted in Alberta, Canada (2002-2006) and included the following groupings of subtypes: MSS = 337 and MSI = 130; type I = 458 and type II = 66. Logistic and polytomous logistic regression were used to estimate odds ratios and 95% confidence intervals for overall endometrial cancer and subtypes of endometrial cancer, respectively. The risks of all subtypes of endometrial cancer, except type II, increased with an increase in all of the anthropometric characteristics examined. The risks for MSI tumors were suggestively stronger than those for MSS tumors; the risk with high (≥30) body mass index (weight (kg)/height (m)(2)) was significantly stronger for MSI tumors (odds ratio = 4.96, 95% confidence interval: 2.76, 8.91) than for MSS tumors (odds ratio = 2.33, 95% confidence interval: 1.66, 3.28) (P-heterogeneity = 0.02). Obesity is associated with most subtypes of endometrial cancer, and further studies are warranted to elucidate the biological mechanisms underlying the stronger risk for the MSI subtype with a high body mass index.

High intakes of dietary sodium are associated with elevated blood pressure levels and an increased risk of cardiovascular disease. National and international guidelines recommend reduced sodium intake in the general population, which necessitates population-wide surveillance. We assessed the utility of casual (spot) urine specimens in estimating 24-hour urinary sodium excretion as a marker of sodium intake in the International Cooperative Study on Salt, Other Factors, and Blood Pressure. There were 5,693 participants recruited in 1984-1987 at the ages of 20-59 years from 29 North American and European samples. Participants were randomly assigned to test or validation data sets. Equations derived from casual urinary sodium concentration and other variables in the test data were applied to the validation data set. Correlations between observed and estimated 24-hour sodium excretion were 0.50 for individual men and 0.51 for individual women; the values were 0.79 and 0.71, respectively, for population samples. Bias in mean values (observed minus estimated) was small; for men and women, the values were -1.6 mmol per 24 hours and 2.3 mmol per 24 hours, respectively, at the individual level and -1.8 mmol per 24 hours and 2.2 mmol per 24 hours, respectively, at the population level. Proportions of individuals with urinary 24-hour sodium excretion above the recommended levels were slightly overestimated by the models. Casual urine specimens may be a useful, low-burden, low-cost alternative to 24-hour urine collections for estimation of population sodium intakes; ongoing calibration with study-specific 24-hour urinary collections is recommended to increase validity.

Investigators in the Chicago Healthy Aging Study (CHAS) reexamined 1,395 surviving participants aged 65-84 years (28% women) from the Chicago Heart Association Detection Project in Industry (CHA) 1967-1973 cohort whose cardiovascular disease (CVD) risk profiles were originally ascertained at ages 25-44 years. CHAS investigators reexamined 421 participants who were low-risk (LR) at baseline and 974 participants who were non-LR at baseline. LR was defined as having favorable levels of 4 major CVD risk factors: serum total cholesterol level <200 mg/dL and no use of cholesterol-lowering medication; blood pressure <120/≤80 mm Hg and no use of antihypertensive medication; no current smoking; and no history of diabetes or heart attack. While the potential of LR status in overcoming the CVD epidemic is being recognized, the long-term association of LR with objectively measured health in older age has not been examined. It is hypothesized that persons who were LR in 1967-1973 and have survived to older age will have less clinical and subclinical CVD, lower levels of inflammatory markers, and better physical performance/functioning and sleep quality. Here we describe the rationale, objectives, design, and implementation of this longitudinal epidemiologic study, compare baseline and follow-up characteristics of participants and nonparticipants, and highlight the feasibility of reexamining study participants after an extended period postbaseline with minimal interim contact.