Most Western chronic diseases are closely tied to lifestyle behaviors, and many are preventable. Despite the well-distributed knowledge of these detrimental behaviors, effective efforts in disease prevention have been lacking. Many of these chronic diseases are related to obesity and type 2 diabetes, which have doubled in incidence during the last 35 years. The Complete Health Improvement Program (CHIP) is a community-based, comprehensive lifestyle modification approach to health that has shown success in addressing this problem. This pilot study demonstrates the effectiveness of CHIP in an underserved, rural, and vulnerable Appalachian population. Two hundred fourteen participants in CHIP collectively demonstrated significant reductions in body mass index, systolic and diastolic blood pressure, and fasting blood levels of total cholesterol, low-density lipoprotein, and glucose. If these results can be repeated in other at-risk populations, CHIP has the potential to help reduce the burden of preventable and treatable chronic diseases efficiently and cost-effectively.
Chronic diseases are on the rise, accounting for 84% of the current national healthcare expenditure [
The Complete Health Improvement Program (CHIP) [
In Appalachia, Athens County is struggling with the highest poverty level in Ohio at 35% [
The study examined the changes in selected chronic disease risk factors of 225 self-selected participants who attended one of six CHIP classes offered in 2011 and 2012 in Athens, Ohio. Approval for the study was obtained from the local CHIP administration and the Ohio University Institutional Review Board.
The CHIP classes were facilitated by volunteers trained and authorized by the Lifestyle Medicine Institute/CHIP through Athens CHIP and were administered locally by Live Healthy Appalachia (LHA), a 501(c)3 organization, located in Athens, Ohio. Each class was conducted over a 4- to 8-week period and involved 16 two-hour group sessions. A typical session included viewing an instructional video, a cooking demonstration, group discussion, and an exercise component. The intent of the intervention was to nurture intelligent self-care through enhanced understanding of the epidemiology, etiology, and risk factors associated with chronic western diseases. The cost of the course covered program tuition, two biomedical assessments (performed at the beginning and near the end of the class), food samples, textbook, workbook, cookbook, water bottle, pedometer, and supplementary reading and reference material.
The primary focus of CHIP was the consumption of whole foods
Although most classes were conducted in 4 weeks, meeting 4 times a week, a couple of classes were extended to 8 weeks, with fewer meetings per week. The course tuition increased incrementally over the time frame covered by the study from $350 to $450. The cost was paid by the participants, by their employer, by a scholarship, or by any combination of these. A limited number of scholarships (for 22 of the 225 participants) were provided by local community organizations and businesses, earmarked for participants with financial need. Scholarship recipients were selected by the local CHIP administration based on interest, expression of need, and eligibility for financial support.
An initial health screen was performed at the beginning of the course. The results were reviewed with the participants to help them understand their risk status and to set goals for the program.
After the second health screen, personal and deidentified aggregated class health screen results were given to each participant to see their individual improvements and how they compared to the group as a whole. This was accompanied by a presentation on the meaning of the results and encouragement to continue with the newly acquired lifestyle changes. Additional copies of results were provided along with encouragement to share these with their primary care provider.
Study participants were self-selected, learning about CHIP via announcements in churches and the local media, or from local health care providers. Potential CHIP participants attended one of several informational sessions presented throughout the community on various dates and times, where they received a mixture of video and live presentations, had their questions addressed, and were offered an opportunity to enroll. All participants in CHIP were informed that their results would be aggregated and reported for research purposes. They were given the option of having their data excluded without affecting their eligibility to participate in CHIP. As shown in Table
The biomedical assessments included weight, height, systolic blood pressure (SBP), and diastolic blood pressure (DBP), obtained by trained medical professionals. Fasting blood samples were collected by trained phlebotomists and analyzed for total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides (TG), and plasma glucose (FPG) utilizing a Beckman Coulter DXC-600 analyzer in the pathology laboratory at O’Bleness Memorial Hospital in Athens, Ohio, a lab certified by the American College of Pathologists,.
Data for each participant was entered into a password protected proprietary Access-based database maintained on the CHIP administration computer at the LHA office as part of the CHIP routine and separate from the data collection for this study. For this study, CHIP administration provided aggregated data from the first six CHIP classes, without personal identifiers, on a password-protected Excel database file.
For both overall and stratified data, means and standard deviations (SD) were computed for each baseline and postintervention. Mean change (baseline mean − postintervention mean) and percent (%) mean change (100 × mean change/baseline mean) were also computed to show magnitudes of changes. One-sample
In this pilot study, a total of 225 people enrolled, with a mean age of 56 years and with a range of 24–81 years, 28% male, 72% females, as displayed in Table
Comparison of gender and mean age distribution in participants attending the Athens, OH, CHIP classes versus those who attended CHIP classes in the US, excluding those attending the Athens classes (Rankin et al. [
Characteristics | Athens | Rankin |
---|---|---|
Total | 225 | 5,066 |
Male | 63 | 1,694 |
Female | 162 | 3,372 |
% male | 28 | 33 |
% female | 72 | 67 |
Age: mean (range) | 56.0 (24–81) | 52.7 (44–71) |
Mean changes in selected risk factors in 225 participants of the Athens, OH, CHIP classes, compared to 5066 participants who participated in CHIP interventions in the US (Rankin et al. [
Variables | Athens (1) | Rankin study (2) |
|
||||||
---|---|---|---|---|---|---|---|---|---|
|
Δ (%) | SD |
|
|
Δ (%) | SD |
| ||
BMI (kg/m2) | 208 | −3.5 | 4.0 | <0.001 | 4536 | −3.2 | 3.0 | <0.001 | >0.2 |
SBP (mmHg) | 203 | −4.7 | 11.5 | <0.001 | 4579 | −4.9 | 18.7 | <0.001 | >0.2 |
DBP (mmHg) | 203 | −1.7 | 13.6 | 0.085 | 4577 | −5.3 | 12.9 | <0.001 | <0.001 |
TC (mg/dL) | 214 | −10.3 | 13.2 | <0.001 | 4674 | −11.0 | 13.8 | <0.001 | >0.2 |
LDL (mg/dL) | 210 | −10.3 | 21.5 | <0.001 | 4568 | −13.0 | 21.1 | <0.001 | 0.080 |
HDL (mg/dL) | 214 | −10.2 | 13.0 | <0.001 | 4673 | −4.7 | 8.8 | <0.001 | <0.001 |
TG (mg/dL) | 214 | 0.0 | 38.0 | >0.2 | 4669 | −7.7 | 42.8 | <0.001 | 0.005 |
FPG (mg/dL) | 213 | −4.1 | 11.1 | <0.001 | 3689 | −6.1 | 21.3 | <0.001 | 0.018 |
(a) Changes in selected chronic disease risk factors according to initial risk classification on 225 participants of the Athens, OH, CHIP. (b) Changes in selected chronic disease risk factors according to initial risk classification on 225 participants of the Athens, OH, CHIP.
Risk factor |
|
|
|
Baseline | Post-intervention | Δ | Δ |
|
Cohen’s | ||
---|---|---|---|---|---|---|---|---|---|---|---|
Baseline | Post-intervention | Mean SD | Mean SD | Mean | % | ||||||
BMI (kg/m2) | |||||||||||
18.5–24.9 | 35 | 51 | 31 (<0.001) | 22.7 | 1.7 | 22.3 | 2.6 | −0.4 | −1.8% | >0.2 | 0.20 |
25–30 | 57 | 58 | 27.3 | 1.3 | 26.1 | 1.4 | −1.2 | −4.4% | <0.001 | 1.90 | |
>30 | 116 | 99 | 37.6 | 6.4 | 36.2 | 6.2 | −1.4 | −3.7% | <0.001 | 1.51 | |
SBP (mmHg) | |||||||||||
<120 | 66 | 104 | 38 (<0.001) | 111.3 | 8.3 | 113.0 | 10.9 | 1.7 | 1.5% | 0.169 | −0.17 |
120–139 | 91 | 78 | 130.3 | 5.6 | 122.7 | 12.1 | −7.6 | −5.8% | <0.001 | 0.64 | |
140–160 | 38 | 19 | 148.8 | 5.6 | 130.4 | 14.4 | −18.4 | −12.4% | <0.001 | 1.29 | |
>160 | 8 | 2 | 170.4 | 10.5 | 150.2 | 21.1 | −20.2 | −11.9% | 0.01 | 1.24 | |
DBP (mmHg) | |||||||||||
<80 | 130 | 154 | 12 (<0.001) | 70.8 | 6.6 | 71.9 | 8.3 | 1.1 | 1.6% | 0.066 | −0.16 |
80–89 | 54 | 39 | 85.0 | 3.3 | 78.9 | 8.1 | −6.1 | −7.2% | <0.001 | 0.74 | |
>90 | 19 | 10 | 94.4 | 2.6 | 82.4 | 8.9 | −12 | −12.7% | <0.001 | 1.39 | |
TC (mg/dL) | |||||||||||
<160 | 51 | 108 | 59 (<0.001) | 141.5 | 15.1 | 133.1 | 27.7 | −8.4 | −5.9% | 0.009 | 0.38 |
160–199 | 97 | 63 | 181.2 | 11.7 | 160.8 | 22.1 | −20.4 | −11.3% | <0.001 | 1.02 | |
200–239 | 47 | 35 | 218.3 | 10.8 | 189.2 | 26.7 | −29.1 | −13.3% | <0.001 | 1.07 | |
240–280 | 16 | 7 | 253.2 | 10.0 | 233.2 | 25.1 | −20 | −7.9% | 0.015 | 0.69 | |
>280 | 3 | 1 | 303 | 29.7 | 216.3 | 55.7 | −86.7 | −28.6% | 0.192 | 1.12 |
Risk factor |
|
|
|
Baseline | Post-intervention | Δ | Δ |
|
Cohen’s | ||
---|---|---|---|---|---|---|---|---|---|---|---|
Baseline | Post-intervention | Mean SD | Mean SD | Mean | % | ||||||
LDL (mg/dL) | |||||||||||
<100 | 78 | 115 | 52 (<0.001) | 78.3 | 18.6 | 72.9 | 23.5 | −5.4 | −6.9% | 0.114 | 0.18 |
100–129 | 67 | 56 | 115.0 | 8.2 | 99.5 | 18.3 | −15.5 | −13.5% | <0.001 | 0.86 | |
130–159 | 46 | 33 | 143.1 | 9.8 | 125.7 | 19.8 | −17.4 | −12.2% | <0.001 | 0.94 | |
160–190 | 14 | 6 | 169.4 | 7.0 | 145.6 | 25.1 | −23.8 | −14.0% | 0.004 | 0.92 | |
>190 | 5 | 0 | 210.6 | 19.2 | 141.4 | 29.1 | −69.2 | −32.9% | 0.015 | 1.83 | |
HDL (mg/dL) | |||||||||||
<40 | 69 | 105 | 60 (<0.001) | 34.9 | 3.7 | 33.4 | 4.6 | −1.5 | −4.3% | 0.004 | 0.36 |
40–60 | 101 | 89 | 48.8 | 5.6 | 42.2 | 7.0 | −6.6 | −13.5% | <0.001 | 1.16 | |
>60 | 44 | 20 | 72.1 | 13.7 | 62.5 | 15.7 | −9.6 | −13.3% | <0.001 | 0.86 | |
TG (mg/dL) | |||||||||||
<100 | 80 | 84 | 1.5 (>0.2) | 71.3 | 19.0 | 81.3 | 32.8 | 10.0 | 14.0% | 0.001 | −0.38 |
100–199 | 102 | 103 | 143.7 | 29.7 | 133.5 | 43.5 | −10.2 | −7.1% | 0.023 | 0.23 | |
200–400 | 29 | 26 | 256.3 | 43.0 | 206.5 | 84.5 | −49.8 | −19.4% | 0.002 | 0.63 | |
>400 | 3 | 1 | 444.7 | 57.6 | 219.0 | 48.9 | −225.7 | −50.8% | 0.019 | 4.16 | |
FPG (mg/dL) | |||||||||||
<110 | 162 | 181 | 15 (<0.001) | 94.7 | 8.8 | 93.2 | 9.1 | −1.5 | −1.6% | 0.021 | 0.18 |
110–125 | 27 | 18 | 116.2 | 4.0 | 108.1 | 11.9 | −8.1 | −7.0% | <0.001 | 0.70 | |
>125 | 24 | 14 | 169.1 | 52.3 | 131.6 | 29.9 | −37.5 | −22.2% | <0.001 | 0.99 |
Table
Table
A comparison of the risk factor reductions observed in this study with those reported by Rankin et al. from CHIP chapters across the United States was similar, as was the data presented in Table
The aim of this study was to validate the effectiveness of CHIP in the rural Appalachian setting of Athens County, Ohio. A total of 225 self-selected participants had the financial resources available to attend the 4- to 8-week intensive, community-based lifestyle intervention program. Chronic disease-related risk factors responded favorably and rapidly to the recommended lifestyle changes towards a healthier whole food, plant-based diet coupled with daily exercise. Those at highest risk had the greatest improvements. The substantial changes in BMI, especially among those in the obesity category, are remarkable in that the program emphasized the unrestricted use of whole foods (fruits, vegetables, whole grains, and legumes) plus plenty of water (to replace carbonated drinks and caffeine). The emphasis was on an
These findings follow those from the Diabetes Prevention Program (DPP), which documented the efficacy of a lifestyle program in those at risk for diabetes [
The overall clinical changes in this pilot study are similar to those found in other 4-week CHIP classes throughout United States [
The significant reductions in TC and LDL may possibly explain the reduction in HDL levels, which is usually considered detrimental. On the other hand, a systematic review and meta-analysis has questioned this. Evaluating 108 randomized trials involving close to 300,000 participants at risk for coronary artery disease (CAD), an international review group concluded that “simply increasing the amount of circulating HDL does not reduce the risk of CAD events, CAD deaths, or total deaths [
Several groups have demonstrated CAD regression [
According to other studies, concurrently with improvement in biomarkers and improved health, the CHIP lifestyle intervention program is cost-effective, reducing medical costs for participants [
Despite the evidence of effectiveness, lifestyle medical treatment is generally underutilized. The prevalent conventional one-to-one, provider-to-patient health care model is significantly limited in the following ways. (1) The time allocated per patient is short, averaging less than 15 minutes, and usually spent addressing problems and prescribing or renewing a different medication for each problem. (2) The model incentivizes the physician to choose the quickest and least time-intensive, but often the most expensive method of evaluation and treatment for the patient. (3) The model is expensive in that it requires highly trained and therefore highly compensated providers to provide basic information that could easily be taught in a more efficient, less expensive way. (4) The model is driven by illness, not by wellness, compensating providers for addressing problems, not for maintaining health. (5) Finally, in many localities, there is a shortage of primary care providers, leaving many who are in need without a medical home to address prevention and easily managed health issues. Left untended, these can then escalate into serious problems, leading the patient to seek care via emergency services, greatly elevating the cost of care.
CHIP, though not generally reimbursed by insurers, historically has utilized trained volunteer facilitators. The facilitators, who are not necessarily medical professionals, present a prepared curriculum in a group setting, achieving remarkable results in reducing biomarkers for illness, medication consumption, and overall health care costs. The content in the videos and printed materials, as well as the feedback from the initial health risk assessment, has been demonstrated to be the key to the success of CHIP. The results of CHIP are less dependent on the training and professional qualification of the facilitator. CHIP can therefore be presented more efficiently and cost-effectively by lower-paid, nonmedical, nonprofessional facilitators in a group setting. It is the final health risk assessment and its consistently favorable clinical outcomes, often accompanied by reductions in medication requirements, as well as the understanding that the participants have become the major contributor to their own health, which provides the needed motivation to maintain the new lifestyle and its health-related benefits.
The magnitude of the observed changes in the biometric risk factors may relate, in part, to the self-selection of the participants. These were people who could afford or obtain funding for the program and thus demonstrated their readiness for a change to improve their health and to assume more personal responsibility for behavioral adjustments, especially in their daily diet. There may also be the confounder of
Athens County is an economically struggling area with the highest poverty rate in Ohio at 35%, with nearly 18% of the population uninsured. To address this need, in 2010, Live Healthy Appalachia became a regional provider of CHIP, attempting to bring better health through education, motivation, and inspiration. This retroactive analysis assessing the cumulative effects of six CHIP classes conducted in the Athens area by LHA has shown that self-selected participants can respond and achieve clinical improvements not dissimilar to those achieved from other sites across the US.
But, can this program be applied to the many people living in poverty in Appalachia with significant health issues, often lacking transportation, adequate education, and easy access to healthcare? Further innovative methods for presentation and application of the principles taught in CHIP may need to be developed and assessed, which will address the needs of people whose situations may hinder their ability to afford, attend, assimilate, and apply the behavioral changes currently taught in CHIP.
The authors declare that there is no conflict of interests regarding the publication of this paper.
This project was completed in cooperation with Live Healthy Appalachia in Athens, Ohio, the local CHIP provider, and Lifestyle Medicine Institute, the owner and producer of CHIP.