Objective This study compared rates of cervical cancer screening and acute care (primary or gynecological) visits among women with and without a diagnosis of psychosis, substance use disorder, bipolar disorder or mania, or depression. Methods Using data about women (N=105,681) enrolled in Maryland's Medicaid program in fiscal year 2005, the authors constructed logistic models with cancer screening and acute care visits as dependent variables and serious mental illness flags as independent variables. Covariates were age, race, geography, Medicaid eligibility category, and sexually transmitted diseases. The logistic model of cervical cancer screening outcomes was repeated with acute care visits as a covariate. Results Women with psychosis (N=4,747), bipolar disorder or mania (N=3,319), or depression (N=5,014) were significantly (p<.05) more likely than women in a control group without such disorders (N=85,375) to receive cancer screening (adjusted odds ratio (AOR) range=1.46–1.78) and to have associated acute care visits (AOR range=1.45–2.15). Compared with those in the control group, women with a substance use disorder, with (N=1,104) or without (N=6,122) psychosis, demonstrated reduced odds of cancer screening (AOR=.80) but similar odds of acute care visits (AOR=1.04). Acute care visits were strongly correlated with cancer screens. Genital cancer prevalence did not significantly differ among diagnostic groups. Conclusions In Maryland Medicaid, the odds of cancer screening and related acute care visits were greater for women with major mental disorders compared with women in the control group. For women with substance use disorders, however, screening was reduced and acute care visits were similar compared with women in the control group. Providers should encourage and support their patients with substance use disorders to increase use of preventive care services by primary care physicians and gynecologists.

Objectives We identified high-priority communities for obesity control efforts in Massachusetts. Methods We developed small-area estimation models to estimate community-level obesity prevalence among community-living adults 18 years or older. Individual-level data from the Behavioral Risk Factors Surveillance System from 1999 to 2005 were integrated with community-level data from the 2000 US Census. Small-area estimation models assessed the associations of obesity (body mass index≥30 kg/m2) with individual- and community-level characteristics. A classification system based on level and precision of obesity prevalence estimates was then used to identify high-priority communities. Results Estimates of the prevalence of community-level obesity ranged from 9% to 38% in 2005 and increased in all communities from 1999 to 2005. Fewer than 7% of communities met the Healthy People 2010 objective of prevalence rates below 15%. The highest prevalence rates occurred in communities characterized by lower income, less education, and more blue-collar workers. Conclusions Similar to the rest of the nation, Massachusetts faces a great challenge in reaching the national obesity control objective. Targeting high-priority communities identified by small-area estimation may maximize use of limited resources.

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