Assessment of possible impact of a health promotion program in Korea from health risk trends in a longitudinally observed cohort

BACKGROUND: Longitudinally observed cohort data can be utilized to assess the potential for health promotion and healthcare planning by comparing the estimated risk factor trends of non-intervened with that of intervened. The paper seeks (1) to estimate a natural transition (patterns of movement between states) of health risk state from a Korean cohort data using a Markov model, (2) to derive an effective and necessary health promotion strategy for the population, and (3) to project a possible impact of an intervention program on health status. METHODS: The observed transition of health risk states in a Korean employee cohort was utilized to estimate the natural flow of aggregated health risk states from eight health risk measures using Markov chain models. In addition, a reinforced transition was simulated, given that a health promotion program was implemented for the cohort, to project a possible impact on improvement of health status. An intervened risk transition was obtained based on age, gender, and baseline risk state, adjusted to match with the Korean cohort, from a simulated random sample of a US employee population, where a health intervention was in place. RESULTS: The estimated natural flow (non-intervened), following Markov chain order 2, showed a decrease in low risk state by 3.1 percentage points in the Korean population while the simulated reinforced transition (intervened) projected an increase in low risk state by 7.5 percentage points. Estimated transitions of risk states demonstrated the necessity of not only the risk reduction but also low risk maintenance. CONCLUSIONS: The frame work of Markov chain efficiently estimated the trend, and captured the tendency in the natural flow. Given only a minimally intense health promotion program, potential risk reduction and low risk maintenance was projected

Feasibility and acceptability of a multiple risk factor intervention: The Step Up randomized pilot trial

<p>Abstract</p> <p>Background</p> <p>Interventions are needed which can successfully modify more than one disease risk factor at a time, but much remains to be learned about the acceptability, feasibility, and effectiveness of multiple risk factor (MRF) interventions. To address these issues and inform future intervention development, we conducted a randomized pilot trial (n = 52). This study was designed to assess the feasibility and acceptability of the Step Up program, a MRF cognitive-behavioral program designed to improve participants' mental and physical well-being by reducing depressive symptoms, promoting smoking cessation, and increasing physical activity.</p> <p>Methods</p> <p>Participants were recruited from a large health care organization and randomized to receive usual care treatment for depression, smoking, and physical activity promotion or the phone-based Step Up counseling program plus usual care. Participants were assessed at baseline, three and six months.</p> <p>Results</p> <p>The intervention was acceptable to participants and feasible to offer within a healthcare system. The pilot also offered important insights into the optimal design of a MRF program. While not powered to detect clinically significant outcomes, changes in target behaviors indicated positive trends at six month follow-up and statistically significant improvement was also observed for depression. Significantly more experimental participants reported a clinically significant improvement (50% reduction) in their baseline depression score at four months (54% vs. 26%, OR = 3.35, 95% CI [1.01- 12.10], <it>p </it>= 0.05) and 6 months (52% vs. 13%, OR = 7.27, 95% CI [1.85 - 37.30], <it>p </it>= 0.004)</p> <p>Conclusions</p> <p>Overall, results suggest the Step Up program warrants additional research, although some program enhancements may be beneficial. Key lessons learned from this research are shared to promote the understanding of others working in this field.</p> <p>Trial registration</p> <p>The trial is registered with ClinicalTrials.gov (<a href="http://www.clinicaltrials.gov/ct2/show/NCT00644995">NCT00644995</a>).</p

Impact of the Prevention Plan on Employee Health Risk Reduction

Abstract This study evaluated the impact of The Prevention Plan? on employee health risks after 1 year of integrated primary prevention (wellness and health promotion) and secondary prevention (biometric and lab screening as well as early detection) interventions. The Prevention Plan is an innovative prevention benefit that provides members with the high-tech/high-touch support and encouragement they need to adopt healthy behaviors. Support services include 24/7 nurse hotlines, one-on-one health coaching, contests, group events, and employer incentives. Specifically, we analyzed changes in 15 health risk measures among a cohort of 2606 employees from multiple employer groups who completed a baseline health risk appraisal, blood tests, and biometric screening in 2008 and who were reassessed in 2009. We then compared the data to the Edington Natural Flow of risks. The cohort showed significant reduction in 10 of the health risks measured (9 at P?≤?0.01 and 1 at P?≤?0.05). The most noticeable changes in health risks were a reduction in the proportion of employees with high-risk blood pressure (42.78%), high-risk fasting blood sugar (31.13%), and high-risk stress (24.94%). There was an overall health risk transition among the cohort with net movement from higher risk levels to lower risk levels (P?<?0.01). There was a net increase of 9.40% of people in the low-risk category, a decrease of 3.61% in the moderate-risk category, and a 5.79% decrease in the high-risk category. Compared to Edington's Natural Flow model, 48.70% of individuals in the high-risk category moved from high risk to moderate risk (Natural Flow 31%), 46.35% moved from moderate risk to low risk (Natural Flow 35%), 15.65% moved from high risk to low risk (Natural Flow 6%), and 87.33% remained in the low-risk category (Natural Flow 70%) (P?<?0.001). (Population Health Management 2010;13:275?284)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85111/1/pop_2010_0027.pd