Declining Trends and Widening Disparities in Overweight and Obesity Prevalence Among Massachusetts Public School Districts, 2009-2014.

OBJECTIVES: We evaluated the overall and sociodemographic disparities in trends in prevalence of childhood overweight and obesity in Massachusetts public school districts between 2009 and 2014. METHODS: In 2009, Massachusetts mandated annual screening of body mass index for students in grades 1, 4, 7, and 10. This was part of the statewide Mass in Motion prevention programs. We assessed trends in the prevalence of overweight and obesity between 2009 and 2014 by district, gender, grade, and district income. RESULTS: From 2009 to 2014, prevalence decreased 3.0 percentage points (from 34.3% to 31.3%) statewide. The 2014 district-level rates ranged from 13.9% to 54.5% (median = 31.2%). When stratified by grade, the decreasing trends were significant only for grades 1 and 4. Although rates of districts with a median household income greater than $37, 000 improved notably, rates of the poorest remain unchanged and were approximately 40%. CONCLUSIONS: Although overall prevalence began to decrease, the geographic and socioeconomic disparities in childhood obesity are widening and remain a public health challenge in Massachusetts. Special efforts should be made to address the needs of socioeconomically disadvantaged districts and to narrow the disparities in childhood obesity.

Patient Characteristics Associated With Smoking Cessation Interventions and Quit Attempt Rates Across 10 Community Health Centers With Electronic Health Records.

OBJECTIVES: We used electronic health record (EHR) data to determine rates and patient characteristics in offering cessation interventions (counseling, medications, or referral) and initiating quit attempts. METHODS: Ten community health centers in New York City contributed 30 months of de-identified patient data from their EHRs. RESULTS: Of 302 940 patients, 40% had smoking status recorded and only 34% of documented current smokers received an intervention. Women and younger patients were less likely to have their smoking status documented or to receive an intervention. Patients with comorbidities that are exacerbated by smoking were more likely to have status documented (82.2%) and to receive an intervention (52.1%), especially medication (10.8%). Medication, either alone (odds ratio [OR] = 1.9; 95% confidence interval [CI] = 1.5, 2.3) or combined with counseling (OR = 1.8; 95% CI = 1.5, 2.3), was associated with higher quit attempts compared with no intervention. CONCLUSIONS: Data from EHRs demonstrated underdocumentation of smoking status and missed opportunities for cessation interventions. Use of data from EHRs can facilitate quality improvement efforts to increase screening and intervention delivery, with the potential to improve smoking cessation rates.

Effect of systems change and use of electronic health records on quit rates among tobacco users in a public hospital system.

OBJECTIVES: We examined electronic health records (EHRs) to assess the impact of systems change on tobacco use screening, treatment, and quit rates among low-income primary care patients in Louisiana. METHODS: We examined EHR data on 79,777 patients with more than 1.2 million adult primary care encounters from January 1, 2009, through January 31, 2012, for evidence of systems change. We adapted a definition of "systems change" to evaluate a tobacco screening and treatment protocol used by medical staff during primary care visits at 7 sites in a public hospital system. RESULTS: Six of 7 sites met the definition of systems change, with routine screening rates for tobacco use higher than 50%. Within the first year, a 99.7% screening rate was reached. Sites had a 9.5% relative decrease in prevalence over the study period. Patients were 1.03 times more likely to sustain quit with each additional intervention (95% confidence interval = 1.02, 1.04). CONCLUSIONS: EHRs can be used to demonstrate that routine clinical interventions with low-income primary care patients result in reductions in tobacco use and sustained quits.

Integrating tobacco cessation quitlines into health care: Massachusetts, 2002-2011.

QuitWorks is a Massachusetts referral program that links health care organizations, providers, and patients to the state's tobacco cessation quitline and provides feedback reporting. Designed collaboratively with all major Massachusetts health plans, QuitWorks was launched in April 2002. In 2010, approximately 340 institutions and practices used QuitWorks. Between April 2002 and March 2011, approximately 3,000 unique providers referred patients and 32,967 tobacco users received referrals. An analysis of QuitWorks data showed 3 phases in referrals between April 2002 and March 2011: referrals increased from April 2002 through November 2005, plateaued during December 2005 through January 2009, then substantially increased during February 2009 through March 2011. Factors responsible include partnerships with stakeholders, periodic program promotions, hospital activities in response to Joint Commission tobacco use measures, service evolutions, provision of nicotine replacement therapy for referred patients, and electronic referral options. QuitWorks' history demonstrates that tobacco cessation referral programs can be successfully sustained over time; reach substantial numbers of tobacco users, benefit providers and health care organizations; and contribute to sustainable systems-level changes in health care.

Access to healthy food stores modifies effect of a dietary intervention.

BACKGROUND: Recent evidence suggests that opening a grocery store in a food desert does not translate to better diet quality among community residents. PURPOSE: This study evaluated the influence of proximity to a healthy food store on the effect of a dietary behavioral intervention on diet among obese adults randomized to either a high fiber or American Heart Association diet intervention. METHODS: Participants were recruited from Worcester County, Massachusetts, between June 2009 and January 2012. Dietary data were collected via 24-hour recalls at baseline and 3, 6, and 12 months post-intervention. Based on in-store inspection data, a store was considered as having adequate availability of healthy foods if it had at least one item available in each of 20 healthy food categories. Linear models evaluated maximum change in dietary outcomes in relation to road distance from residence to the nearest June healthy food store. The analysis was conducted in January to June 2014. RESULTS: On average, participants (N=204) were aged 52 years, BMI=34.9, and included 72% women and 89% non-Hispanic whites. Shorter distance to a healthy food store was associated with greater improvements in consumption of fiber (b=-1.07 g/day per mile, p<0.01) and fruits and vegetables (b=-0.19 servings/day per mile, p=0.03) with and without covariate adjustment. CONCLUSIONS: The effectiveness of dietary interventions is significantly influenced by the presence of a supportive community nutrition environment. Considering the nationwide efforts on promotion of healthy eating, the value of improving community access to healthy foods should not be underestimated. CLINICAL TRIAL REGISTRATION NUMBER: NCT00911885.

The effect of systematic clinical interventions with cigarette smokers on quit status and the rates of smoking-related primary care office visits.

BACKGROUND: The United States Public Health Service (USPHS) Guideline for Treating Tobacco Use and Dependence includes ten key recommendations regarding the identification and the treatment of tobacco users seen in all health care settings. To our knowledge, the impact of system-wide brief interventions with cigarette smokers on smoking prevalence and health care utilization has not been examined using patient population-based data. METHODS AND FINDINGS: Data on clinical interventions with cigarette smokers were examined for primary care office visits of 104,639 patients at 17 Harvard Vanguard Medical Associates (HVMA) sites. An operational definition of "systems change" was developed. It included thresholds for intervention frequency and sustainability. Twelve sites met the criteria. Five did not. Decreases in self-reported smoking prevalence were 40% greater at sites that achieved systems change (13.6% vs. 9.7%, p<.01). On average, the likelihood of quitting increased by 2.6% (p<0.05, 95% CI: 0.1%-4.6%) per occurrence of brief intervention. For patients with a recent history of current smoking whose home site experienced systems change, the likelihood of an office visit for smoking-related diagnoses decreased by 4.3% on an annualized basis after systems change occurred (p<0.05, 95% CI: 0.5%-8.1%). There was no change in the likelihood of an office visit for smoking-related diagnoses following systems change among non-smokers. CONCLUSIONS: The clinical practice data from HVMA suggest that a systems approach can lead to significant reductions in smoking prevalence and the rate of office visits for smoking-related diseases. Most comprehensive tobacco intervention strategies focus on the provider or the tobacco user, but these results argue that health systems should be included as an integral component of a comprehensive tobacco intervention strategy. The HVMA results also give us an indication of the potential health impacts when meaningful use core tobacco measures are widely adopted.

Who underreports smoking on birth records: a Monte Carlo predictive model with validation.

BACKGROUND: Research has shown that self-reports of smoking during pregnancy may underestimate true prevalence. However, little is known about which populations have higher rates of underreporting. Availability of more accurate measures of smoking during pregnancy could greatly enhance the usefulness of existing studies on the effects of maternal smoking offspring, especially in those populations where underreporting may lead to underestimation of the impact of smoking during pregnancy. METHODS AND FINDINGS: In this paper, we develop a statistical Monte Carlo model to estimate patterns of underreporting of smoking during pregnancy, and apply it to analyze the smoking self-report data from birth certificates in the state of Massachusetts. Our results illustrate non-uniform patterns of underreporting of smoking during pregnancy among different populations. Estimates of likely underreporting of smoking during pregnancy were highest among mothers who were college-educated, married, aged 30 years or older, employed full-time, and planning to breastfeed. The model's findings are validated and compared to an existing underreporting adjustment approach in the Maternal and Infant Smoking Study of East Boston (MISSEB). CONCLUSIONS: The validation results show that when biological assays are not available, the Monte Carlo method proposed can provide a more accurate estimate of the smoking status during pregnancy than self-reports alone. Such methods hold promise for providing a better assessment of the impact of smoking during pregnancy.