martes, 17 de octubre de 2017

Implementation of Best Practices in Obesity Prevention in Child Care Facilities: The Arizona Empower Program, 2013–2015

Implementation of Best Practices in Obesity Prevention in Child Care Facilities: The Arizona Empower Program, 2013–2015

Centers for Disease Control and Prevention. CDC twenty four seven. Saving Lives, Protecting People



Implementation of Best Practices in Obesity Prevention in Child Care Facilities: The Arizona Empower Program, 2013–2015

Jillian Papa, MPH1; Joan Agostinelli, MA1; Gertrudes Rodriguez, MBA, RD1; Deborah Robinson, MPH, RD1 (View author affiliations)

Suggested citation for this article: Papa J, Agostinelli J, Rodriguez G, Robinson D. Implementation of Best Practices in Obesity Prevention in Child Care Facilities: The Arizona Empower Program, 2013–2015. Prev Chronic Dis 2017;14:160451. DOI: http://dx.doi.org/10.5888/pcd14.160451.
PEER REVIEWED

Abstract

Introduction
Obesity is a major health concern in every US age group. Approximately one in 4 children in Arizona’s Special Supplemental Nutrition Program for Women, Infants, and Children is overweight or obese. The Arizona Department of Health Services developed the Empower program to promote healthy environments in licensed child care facilities. The program consists of 10 standards, including one standard for each of these 5 areas: physical activity and screen time, breastfeeding, fruit juice and water, family-style meals, and staff training. The objective of this evaluation was to determine the level of implementation of these 5 Empower standards.
Methods
A self-assessment survey was completed from July 2013 through June 2015 by 1,850 facilities to evaluate the level of implementation of 5 Empower standards. We calculated the percentage of facilities that reported the degree to which they implemented each standard and identified common themes in comments recorded in the survey.
Results
All facilities reported either full or partial implementation of the 5 standards. Of 1,678 facilities, 21.7% (n = 364) reported full implementation of all standards, and 78.3% (n = 1,314) reported at least partial implementation. Staff training, which has only one component, had the highest level of implementation: 77.4% (n = 1,299) reported full implementation. Only 44.0% (n = 738) reported full implementation of the standard on a breastfeeding-friendly environment.
Conclusion
Arizona child care facilities have begun to implement the Empower program, but facilities will need more education, technical assistance, and support in some areas to fully implement the program.
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Introduction

The US Surgeon General recognizes obesity as a major health concern (1). Obese children as young as 2 to 5 years are more likely than children who are not obese at that age to become obese adults (2). Approximately one in 4 children aged 2 through 4 years enrolled in Arizona’s Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is overweight or obese (3).
Approximately 80% of preschool-aged children spend as much as 40 hours per week in nonparental care (4). National recommendations have established the early care and education setting as an important opportunity for obesity intervention (5). Evaluations of obesity prevention interventions in child care facilities show improvements in children’s mealtime behaviors, dietary preferences, and levels of physical activity (4).
Several prominent authorities collaboratively published national standards for best practices in 2010 (6). The Empower program, based on these national standards, was implemented in 2010 to promote healthy environments for children in Arizona’s licensed child care facilities. Participating facilities receive discounted licensing fees for their agreement to follow the program’s 10 standards (Box).

Box. Ten Empower Standards to Improve Health in Licensed Child Care Facilities in Arizonaa,b.

Standard 1. Provide at least 60 minutes of daily physical activity, and do not allow more than 3 hours of screen time per week.
Standard 2. Practice sun safety.
Standard 3. Provide a breastfeeding-friendly environment.
Standard 4. Determine whether site is eligible for the US Department of Agriculture Child and Adult Care Food Program.
Standard 5. Limit serving fruit juice.
Standard 6. Serve meals family style.
Standard 7. Provide monthly oral health care education or implement a tooth-brushing program.
Standard 8. Ensure that staff members receive 3 hours of training annually on Empower topics.
Standard 9. Make Arizona Smokers’ Helpline (ASHLine) education materials available at all times.
Standard 10. Maintain a smoke-free campus.
a Data source: Arizona Department of Health Services Bureau of Nutrition and Physical Activity (7).
b Implementation of standards in boldface were evaluated in this study.
The objective of this evaluation was to determine the level of implementation of the 5 Empower standards that relate to obesity prevention: the standards on physical activity and screen time, breastfeeding, fruit juice and water, and family-style meals, and the standard on staff training. We hypothesized that none of the standards would have been implemented across all participating facilities.
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Methods

We designed a self-assessment survey to collect data from licensed child care facilities enrolled in Arizona’s Empower program between July 1, 2013, and June 30, 2015.
Child care facilities volunteer to implement 10 Empower standards. As part of the program, participating facilities receive the Empower guidebook (7), a reference manual on early care and education best practices and national recommendations (6,8), and documents on state rules and regulations (9,10). The guidebook defines key terms related to standards and provides age-specific guidance and adaptations for special circumstances. Examples of policies and materials were also provided for staff education, family engagement, and marketing to assist with implementation.
The Arizona Department of Health Services (ADHS) inspects all types of licensed child care facilities at least once annually. The data for this study were collected during the first inspection completed for each participating facility during the 2-year study period. At least one assessment was completed by 1,862 facilities. Data for 12 facilities were excluded because the provider identification number did not match information in the licensing database, which we used to verify the identity of each facility and its enrollment capacity. Our sample consisted of 1,850 facilities serving 182,602 children.
Surveyors from the ADHS Bureau of Child Care Licensing collected data from a facility staff member during their annual on-site inspections. In year 1, electronic tablets and paper surveys were used to collect data, which were then entered into an Excel (Microsoft Corp) form. Surveyors requested paper surveys in year 2; data from these surveys were also entered into an Excel form. These data were then compiled into an Empower database in Excel. Surveyors also recorded comments from facility staff.
The data collection tool was a self-administered survey that asked facilities to self-report their level of implementation on each component of each standard. Four of the 5 standards consist of more than one component: physical activity and screen time (10 components), breastfeeding (4 components), fruit juice and water (7 components), and family-style meals (6 components). The fifth standard, staff training, has only one component. Each component represents a discrete, observable aspect of the standard.
We conducted 3 levels of analysis: by component, by standard, and by facility. Proportions were calculated for each component, standard, and facility by using SPSS version 24 (IBM Corp). For the analysis by component, each component was examined for its level of implementation as either full, partial, or not at all. Missing values and responses of “don’t know” were combined into one category. Because the staff training standard has only one component, we did not analyze this standard by component.
For the analysis by standard, we categorized each standard into an overall rating across its components. A standard was categorized as fully implemented when a facility reported fully implementing all of the components of the standard. The standard was categorized as not at all being implemented when a facility reported implementation of all components of the standard as “not at all.” If a facility reported any other mix of ratings across components, the standard was categorized as partially implemented. Components with missing values and responses of “don’t know” were excluded from the analyses by standard. The analysis by standard consisted of 1,678 assessments.
For the analysis by facility, we calculated the percentage of facilities that implemented standards fully, partially, or not at all. A facility was classified as fully implemented if all standards were rated as fully implemented. Facilities that had implemented none of the standards were classified as “not at all” implemented. Any facility with any other combination of fully or partially implemented standards was classified as partially implemented. Components with missing values and responses of “don’t know” were excluded from the analyses by facility. The analysis by facility consisted of 1,678 assessments.
We conducted a content analysis of comments by using QDA Miner version 4.0 (Provalis Research). We identified themes and developed codes for analysis. The 1,850 assessments offered 283 comments; we excluded 77 comments because they were not relevant to the study. The remaining 206 comments were classified into one of 6 categories (general Empower program and the 5 standards) and then analyzed for themes.
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Results

In the analysis by facility, all 1,678 facilities reported either full or partial implementation of all 5 standards. About one-fifth (21.7%; n = 364) of facilities reported full implementation of all standards, and 78.3% (n = 1,314) of facilities reported at least partial implementation. In the analysis by standard, the percentage of child care facilities reporting full implementation ranged from 44.0% (n = 738), for the breastfeeding-friendly environment, to 77.4% (n = 1,299) for staff training (Figure). In the analysis by component (Table), the level of full implementation ranged from 45.6% (provides breastfeeding information to families) to 97.9% (offers water as the first choice for thirst). Four standards had a component on providing information to families; these components had the lowest levels of implementation. We observed the highest levels of implementation for the standard on fruit juice and water.

Level of implementation, by standard, of Arizona Licensed Child Care Facilities Empower standards reported by 1,678 child care facilities, July 2013–June 2015. Components with missing values and responses of “don’t know” were excluded from the analyses by standard. Four standards have multiple components; the staff training standard has only one component.
Figure.
Level of implementation, by standard, of Arizona Licensed Child Care Facilities Empower standards reported by 1,678 child care facilities, July 2013–June 2015. Components with missing values and responses of “don’t know” were excluded from the analyses by standard. Four standards have multiple components; the staff training standard has only one component. [A tabular version of this figure is also available.]
Of the 206 relevant comments, 92.7% (n = 191) were from surveys completed during the first year of the 2-year study period. Seventy-five comments related to the Empower program in general; of these, 33 (44.0%) comments related to the process of developing policies; 35 (46.7%) comments related to being new to the program and not receiving, or only recently receiving, the guidebook; 3 (4.0%) comments related to changes in personnel; and 4 (5.3%) comments indicated that the respondent did not know if the facility had a policy. The other 139 relevant comments related to one of the 5 standards and are summarized below.
Physical activity and screen time. Nearly half (46.3%) of facilities reported fully implementing all 10 components of the standard on physical activity and screen time (Figure). Most reported fully implementing the component on providing free-play opportunities (92.5%) and outdoor activity (91.1%), and 67.2% reported fully implementing the component on providing vigorous physical activity. Providing information on screen time to families had the lowest level of implementation (67.0%). Of the 55 comments on physical activity and screen time, 11 (20.0%) comments related to the need to clarify language or confusion about components, and 14 (25.5%) comments related to facilities not being all-day centers. Some respondents asked about the definitions of words such as vigorous, moderate, sedentary, and screen time. Other comments related to a facility being a partial-day facility or not having an outdoor playground.
Breastfeeding-friendly environment. The breastfeeding-friendly environment standard had the lowest level of implementation. Only 44.0% of facilities reported full implementation, and 20.7% reported that they had not implemented any components. The lowest component scores for this standard were in providing information to families (45.6%) and displaying information (47.8%). Of the 76 comments related to breastfeeding-friendly environments, most (67.1%) indicated that the respondent’s facility did not provide care for infants and 16 (21.1%) indicated that the standard was not applicable.
Fruit juice and water. More than half (53.3%) of facilities reported fully implementing all of the components of the standard on fruit juice and water. Nearly all reported full implementation of 2 components: offering water throughout the day (98.6%) and offering water as the first choice for thirst (97.9%). Most (91.4%) facilities reported fully implementing the component for serving only 100% fruit juice. The component for providing information on fruit juice and water to families had the lowest level of implementation, with only 59.7% of facilities reporting full implementation. Of the 37 comments related to the standard on fruit juice and water, 27 (73.0%) indicated not serving fruit juice at all.
Family-style meals. More than half (59.7%) of facilities reported fully implementing all components of family-style meals. Most (93.2%) reported full implementation of the component for prohibiting the use of food as punishment or reward, and most (91.2%) required staff participation in meals. More than four-fifths fully implemented the components for using child-friendly serving utensils (85.7%) and allowing children to choose what and how much to eat (83.4%). The component of this standard with the lowest level of implementation was providing information to families (78.4%). Of the 35 comments related to family-style meals, 18 (51.4%) were about children bringing their own food from home. Three comments were about not serving food at all (8.6%).
Staff training. The staff training standard had the highest percentage (77.4%) of facilities reporting full implementation. We found 3 comments on staff training.
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Discussion

Approximately one in 5 licensed child care facilities in Arizona reported full implementation of all 10 standards of the Empower program; most facilities reported at least partially implementing them. Survey comments suggested that many facilities were not familiar with the Empower guidebook, especially the sections explaining key terms related to physical activity and offering guidance on partial days and indoor play. It appears that more training and technical assistance are needed on these topics. Future training and technical assistance will focus on educating facility staff members on these topics, which are fundamental in transforming the early care and education setting to support healthy behaviors (11).
A breastfeeding-friendly environment is another important area of focus for obesity prevention. Observational studies suggest that the first 2 years of life are an optimal time in which to prevent obesity by establishing positive eating behaviors (12). They also suggest that breastfeeding has a promising role in preventing childhood obesity (13,14). The Empower breastfeeding standard focuses on creating a breastfeeding-friendly environment (7), which applies to all child care facilities, even if they do not serve infants. This standard had the lowest rate of implementation, with comments indicating that many thought the standard did not apply to facilities that did not care for infants. These comments suggest that facilities will need additional training and technical assistance on this topic. Child care staff members may need a place to express and store breastmilk for their own breastfeeding children who are not at the facility. Alternatively, a mother of an older enrolled child may need a private lactation area to breastfeed a younger sibling. A breastfeeding-friendly environment should not be limited to facilities that enroll infants.
Arizona’s standard on fruit juice is more restrictive than the national recommendation to serve no more than 4 to 6 ounces of fruit juice per day to children aged one to 6 years (6). Arizona’s standard requires no more than 2 four-ounce servings of 100% fruit juice per week be given to children aged one to 6, unless it is appropriate for a child’s special health care need (7). Water and milk are the preferred beverages for meals and snacks (7). Nearly all facilities reported full implementation of components for offering water throughout the day and offering water as the first choice for thirst. Arizona’s revised statutes on fruit and fruit juice align with national recommendations; however, Empower standards exceed those requirements. Empower training in standards on accessible and abundant water is especially emphasized in Arizona because of the potential for dehydration in extreme temperatures. It is critically important to comply with this requirement in Arizona, where temperatures in the shade frequently measure more than 110°F.
The Institute of Medicine recommends that child care providers practice responsive feeding, which includes self-regulation of intake by infants and allowing toddlers and preschoolers to serve themselves from common bowls (family-style service) (15). This practice encourages children to eat according to their own hunger and fullness cues (16) and develop their hand–eye coordination skills. Additionally, the presence of an adult facilitates learning about nutrition and can lead to pleasant mealtimes (6). Implementation levels for serving meals family-style were relatively high among the facilities studied.
Parents and families are role models and strongly influence young children’s eating and activity environments (14,17). Communication between child care staff and parents is important to promote healthy weight in children (4). Each standard includes a component on providing information to the family, and we found that this component had the lowest level of implementation in each standard, indicating a need for specific, standardized educational materials for all facilities to display, disseminate, and have available for families. Anecdotal feedback from monthly meetings with the licensing surveyors indicated that child care staff were receptive to distributing and posting colorful educational materials. They suggested that providing a variety of educational information on a regular basis could help improve family engagement on Empower topics.
A strength of the study is the size of the sample. The ADHS Bureau of Nutrition and Physical Activity leveraged a unique partnership with the Bureau of Child Care Licensing to administer the assessments as part of its routine site inspections. By embedding the assessments into licensing processes, we were able to collect data throughout the state using fewer resources and less time than we would have used otherwise. The Bureau of Child Care Licensing surveyors also were able to offer education and technical assistance to encourage facilities to implement standards. Other states may want to explore this type of opportunity with their child care regulatory agencies to leverage similar efforts.
Our study had several limitations, including selection and response biases. That facilities volunteered to implement the 10 standards and participate in the program is a selection bias. Discounted licensing fees provided a monetary incentive to overstate levels of implementation. In addition, the self-assessment was part of a site inspection in which a reviewer had authority to sanction noncompliance of official rules. These factors exerted potentially strong external pressures toward favorable responses. The Empower survey had never been used before and has not been validated. It was a self-assessment, and there was no way to know how closely a respondent’s self-reported responses corresponded with their actual practices. The survey did not have an option for “does not apply” because standards were designed to apply to all settings. Although modifications of standards are permitted for the unique aspects of some sites, the survey did not account for these modifications. Finally, this evaluation was limited to ADHS-licensed child care facilities, and our findings might not generalize to other early care and education settings in or outside Arizona.
Despite these limitations, our results provide insights into an ongoing statewide effort to implement the Empower program in licensed child care facilities and provide baseline data against which future measures can be assessed. Low levels of implementation in providing information to families show a need to develop standard educational materials for families, while state requirements have led to high levels of implementation for the most stringent standards, such as fruit juice and water, suggesting that family engagement should be a focus of further study. Our findings will be used in Arizona to more effectively promote policy, system, and environmental changes in child care settings, which have the potential to improve the health of and reduce obesity rates among preschool-aged children in Arizona. The program is still in a capacity-building phase, and it is too early to assess its effect on childhood obesity rates.
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Acknowledgments

This publication was supported, in part, by cooperative agreement no. DP004793 from the Centers for Disease Control and Prevention (CDC). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC or the US Department of Health and Human Services (DHHS). The Empower program is supported through funding provided by the DHHS Title V Maternal and Child Health Services Block Grant, CDC 1305, US Department of Agriculture Supplemental Nutrition Assistance Program–Education, Arizona’s First Things First program, and Arizona lottery and tobacco tax revenue. In-kind support of Empower standards is provided by the ADHS’s bureaus of Child Care Licensing, Nutrition and Physical Activity, Tobacco and Chronic Disease, and Women’s and Children’s Health; the Office of Environmental Health; and the Arizona Department of Education. We thank Dr Kathleen Whitten for her extensive consultation on this article and ICF International for its web-based training series on manuscript development.
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Author Information

Corresponding Author: Joan Agostinelli, MA, Agostinelli Consulting LLC, 2908 N 82nd St, Scottsdale, AZ 85251. Telephone: 602-803-4677. Email: Joan.agostinelli@azdhs.gov.
Author Affiliations: 1Arizona Department of Health Services, Phoenix, Arizona.
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References

  1. US Department of Health and Human Services. The Surgeon General’s vision for a healthy and fit nation. Rockville (MD): US Department of Health and Human Services, Office of the Surgeon General; 2010.
  2. Freedman DS, Khan LK, Serdula MK, Dietz WH, Srinivasan SR, Berenson GS. The relation of childhood BMI to adult adiposity: the Bogalusa Heart Study. Pediatrics 2005;115(1):22–7.CrossRef PubMed
  3. Arizona Department of Health Services Bureau of Nutrition and Physical Activity. WIC needs assessment. The Arizona WIC program. http://azdhs.gov/documents/prevention/azwic/wic-needs-assessment-02-22-13.pdf. Published February 22, 2013. Accessed August 30, 2016.
  4. Larson N, Ward DS, Neelon SB, Story M. What role can child-care settings play in obesity prevention? A review of the evidence and call for research efforts. J Am Diet Assoc 2011;111(9):1343–62. CrossRef PubMed
  5. Reynolds MA, Jackson Cotwright C, Polhamus B, Gertel-Rosenberg A, Chang D. Obesity prevention in the early care and education setting: successful initiatives across a spectrum of opportunities. J Law Med Ethics 2013;41(Suppl 2):8–18. CrossRef PubMed
  6. Preventing childhood obesity in early care and education: Selected Standards From Caring for Our Children: National Health and Safety Performance Standards; Guidelines for Early Care and Education Programs, 3rd edition. Aurora (CO): American Academy of Pediatrics, American Public Health Association, and National Resource Center for Health and Safety in Child Care and Early Education; 2010.
  7. Arizona Department of Health Services Bureau of Nutrition and Physical Activity. Empower guidebook. Ten ways to empower children to live healthy lives. Standards for Empower child care facilities in Arizona. 2nd edition. http:/www.theempowerpack.org. Accessed July 24, 2016.
  8. Let’s Move! Child Care. https://healthykidshealthyfuture.org. Accessed July 24, 2016.
  9. Arizona Department of Health Services Bureau of Child Care Licensing. Arizona administrative code and Arizona revised statutes for child care facilities. http://azdhs.gov/documents/licensing/childcare-facilities/rules/bccl-child-care-facility-rules.pdf. Accessed August 23, 2016.
  10. Arizona Department of Health Services Bureau of Child Care Licensing. Arizona administrative code and Arizona revised statutes for child care group homes. http://azdhs.gov/documents/licensing/childcare-facilities/rules/bccl-child-care-group-home-rules.pdf. Accessed August 23, 2016.
  11. Trost SG, Messner L, Fitzgerald K, Roths B. Nutrition and physical activity policies and practices in family child care homes. Am J Prev Med 2009;37(6):537–40. CrossRef PubMed
  12. Ciampa PJ, Kumar D, Barkin SL, Sanders LM, Yin HS, Perrin EM, et al. Interventions aimed at decreasing obesity in children younger than 2 years: a systematic review. Arch Pediatr Adolesc Med 2010;164(12):1098–104. CrossRef PubMed
  13. Bernardo H, Cesar V. Long-term effects of breastfeeding: a systematic review. Geneva (CH): World Health Organization; 2013. http://www.who.int/iris/handle/10665/79198. Accessed August 23, 2016.
  14. Allen KL, Gibson LY, McLean NJ, Davis EA, Byrne SM. Maternal and family factors and child eating pathology: risk and protective relationships. J Eat Disord 2014;2(1):11. CrossRefPubMed
  15. Early childhood obesity prevention policies. Washington (DC): Institute of Medicine; 2011.
  16. Branen LJ, Fletcher JW, Myers LS. Effects of pre-plated and family-style food service on preschool children’s food intake and waste at snacktime. J Res Child Educ 1997;12(1):88–95.CrossRef
  17. Daniels LA, Mallan KM, Nicholson JM, Thorpe K, Nambiar S, Mauch CE, et al. An early feeding practices intervention for obesity prevention. Pediatrics 2015;136(1):e40–9. CrossRefPubMed

Differences Between Younger and Older US Adults With Multiple Chronic Conditions

Differences Between Younger and Older US Adults With Multiple Chronic Conditions

Centers for Disease Control and Prevention. CDC twenty four seven. Saving Lives, Protecting People



Differences Between Younger and Older US Adults With Multiple Chronic Conditions

Mary L. Adams, MS, MPH

Suggested citation for this article: Adams ML. Differences Between Younger and Older US Adults With Multiple Chronic Conditions. Prev Chronic Dis 2017;14:160613. DOI: http://dx.doi.org/10.5888/pcd14.160613.
PEER REVIEWED

Abstract

Introduction
Adults with multiple (≥2) chronic conditions (MCCs) account for a large portion of US health care costs. Despite the increase in MCC rates with age, most people with MCCs are working age. The study objective was to compare adults with MCCs who were younger than 65 years with those aged 65 years or older on selected measures to better understand the differences between groups and inform interventions that could lower health care costs.
Methods
Data from respondents to the 2015 Behavioral Risk Factor Surveillance System data (N = 201,711) were used to compare adults aged 65 or older with MCCs with those younger than 65 with MCCs in unadjusted and adjusted analyses on chronic conditions, quality of life measures, disability status, access to health care, and modifiable risk factors. MCCs were based on up to 12 chronic conditions (heart disease, stroke, asthma, arthritis, chronic obstructive pulmonary disease, high cholesterol, cognitive impairment, diabetes, depression, chronic kidney disease, cancer other than skin, and hypertension).
Results
Consistent with 80% of all adults being younger than 65, more than 60% of adults with MCCs were younger than 65 years. Compared with adults aged 65 or older with MCCs, those younger than 65 were more likely to report asthma, cognitive impairment, depression, smoking, obesity, poorer access to health care, disability, and worse quality of life in both unadjusted and adjusted analysis.
Conclusion
To decrease the burden of chronic diseases, adults younger than 65 with MCCs should get the treatment they need to reduce the chance of developing more chronic conditions as they age. The ultimate goal is to improve health status and reduce health care costs for everyone with MCCs.
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Introduction

Rates of multiple chronic conditions (MCCs), defined as having 2 or more co-occurring chronic conditions, tend to increase with age (1), resulting in increasing Medicare costs (2). As a consequence, considerable information on MCCs comes from Medicare claims data (3,4) for adults aged 65 years or older. A recent review of 163 studies (5) that included adults of all ages noted that despite the increase in MCC rates with age, most people with MCCs are working age. Other studies found that medical expenditures for chronic conditions among nonelderly adults and adults aged 65 or older were similar, averaging approximately $3,700 for those with 2 or 3 chronic conditions and $8,900 for those with 4 or more (6). Another study (7) found larger relative increases in MCCs over time among those aged 25 to 44 years compared with older adults and different chronic conditions by age group.
Lifestyle factors such as smoking and obesity (8–10) increase the risk of many chronic conditions included in measures of MCCs. Some chronic conditions, such as diabetes, depression, high blood pressure, and high cholesterol, are also risk factors for MCCs (5). Any of these risk factors can increase the likelihood of developing additional chronic conditions in adults of any age. When considered collectively, these findings suggest the need for a better understanding of MCCs among younger adults to develop effective strategies to prevent more chronic conditions from developing and better manage existing ones. This understanding in turn could mitigate any increase in future health care costs.
The objective of this study was to compare adults younger than 65 with MCCs with those aged 65 years or older with MCCs on selected measures. Measures included disability status, quality of life measures, chronic conditions, risk factors, and access to health care to add to information that is known about adults younger than 65 with MCCs. Because there is no standard list of chronic conditions to include, the study used different definitions of MCCs: one that considers diabetes, high blood pressure, high cholesterol, and depression as chronic conditions, and one that does not.
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Methods

We examined data from the 2015 Behavioral Risk Factor Surveillance System (BRFSS) data (11) on 434,382 respondents aged 18 years or older in the 50 states and the District of Columbia. BRFSS data have been shown to be comparable to those of other surveys, with most self-reported measures showing good or better validity (12). For all measures used, responses of “don’t know” or refusal to answer were excluded. The median response rate for cellular telephone and landline surveys combined for the 50 states and the District of Columbia was 46.6%, ranging from 33.9% in California to 61.1% in Utah (13). Data were weighted to be representative of the total adult population of each state by age, race/ethnicity, sex, marital status, education, home ownership, and type of telephone service. Chronic conditions were chosen to be as consistent as possible with commonly cited lists (14,15) and availability on the BRFSS. The MCC based on 5 chronic conditions (MCC5) included cardiovascular disease (CVD; heart attack, angina, coronary heart disease, or stroke), asthma, chronic obstructive pulmonary disease (COPD), arthritis, and cognitive impairment while MCC12 split CVD into heart disease and stroke and added diabetes, high blood pressure, depression, high cholesterol, chronic kidney disease, and cancer other than skin. All chronic conditions except cognitive impairment were defined as having “ever been told”; women who were told they had diabetes only when pregnant were considered not to have diabetes. Cognitive impairment was defined as a yes response to “Because of a physical, mental, or emotional problem, do you have difficulty remembering, concentrating, or making decisions?” This question has been asked by the US Census Bureau since 2008 and is now asked as 1 of 6 disability questions on all federal surveys (16). This cognitive impairment measure is consistent with other measures of cognitive impairment but should not be considered cognitive decline, because the question lacks a time frame (17,18). Respondents who reported any 2 or more of the 5 chronic conditions were considered to have MCC5 (n = 69,487), and those who reported any 2 or more of the 12 were considered to have MCC12 (n = 201,711).
Demographic measures were sex, age (18–64 y and ≥65 y), race/ethnicity (non-Hispanic white, black or African American, Hispanic of any race, American Indian/Alaska Native, and other), education level (college graduate, some college, high school graduate, <high school graduate), annual household income (≥$75,000, $50,000–$74,999, $25,000–$49,999, $15,000–24,999, <$15,000, or unknown), and employment status (employed/self-employed, out of work, homemaker, student, retired, or unable to work). The list of measures that were compared by age group included each of the chronic conditions included in the MCCs; disability (limited in any way in any activities because of physical, mental, or emotional problems); 4 difficulty measures (difficulty seeing, walking, bathing or dressing, or doing errands alone); obesity (body mass index ≥30 kg/m2 based on self-reported height and weight); current smoking; no leisure time physical activity (in the past month); no health insurance; no personal physician; a barrier to health care (needing to see a doctor in past year but unable to because of cost); having a routine check-up in the past 2 years; and quality of life measures including fair or poor general health, frequent (14 or more days in the past 30 days) poor mental health (referred to as frequent mental distress [FMD]), frequent poor physical health (FPD), and frequent activity limitation (FAL).
Stata version 14.1 (StataCorp LP) was used for all weighted data analysis to account for the complex sample design of the BRFSS, and Pearson χ2 tests were used to determine significance at P<.05. Age group comparisons (<65 y vs ≥65 y) were made for adults with MCC12 and those without MCC12 and also for adults with MCC5. Logistic regression was conducted, controlling for demographic and other selected measures, to confirm unadjusted results.
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Results

The weighted percentage of all survey respondents younger than age 65 was 80.3% (Table 1). Although the percentage of adults with MCCs who were younger than age 65 was less than that for all adults, 61.4% of adults with MCC5 and 63.8% with MCC12 were younger than 65 years. Other demographic, health status, and insurance status characteristics varied between all adults and those with MCCs. Results of age group comparisons (Table 2) indicated that compared with adults aged 65 or older, younger adults were more likely to report a total of 18 measures including 10 that showed similar results for adults with and without MCC12 and 8 that only showed significantly worse results among adults ages 18 to 64 years with MCC12 (5 measures related to disability and 3 indicating poorer quality of life). Although adults with and without MCC12 were not directly compared, for all measures except health care access, adults with MCC12 in both age groups appeared worse off than those without MCC12 (Table 2). Results for measures among adults with MCC5 were similar but often higher for both age groups compared with results for MCC12 (Appendix).
Logistic regression analysis for the 10 measures that showed similar results for adults with and without MCC12 resulted in adjusted odds ratios (AORs) comparing younger with older adults that ranged from 1.49 (95% confidence interval [CI], 1.36–1.63) for FMD to 4.79 (95% CI, 4.01–5.71) for being uninsured (Table 3). For the 8 outcomes that showed significant age differences among adults with MCC12 but not among those without MCC12, only the AORs for disability, fair or poor general health, FAL, and being unable to work that compared respondents aged 18 to 64 years versus those aged 65 years or older among adults with MCC12 were higher than 1.00 (Table 3). AORs comparing non-elderly versus elderly adults with MCC12 for difficulty seeing and FPD were not significantly different from 1.00, but AORs for difficulty dressing and running errands were less than 1.00 indicating adults aged 65 or older with MCC12 were more likely to report those outcomes. Results for MCC5 were similar to those for MCC12 (Appendix).
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Discussion

Among adults with 2 MCCs there were significant differences by age group in 18 measures, indicating that adults younger than 65 were worse off than adults aged 65 or older. Results were similar whether diabetes, depression, hypertension, high cholesterol (which could also be risk factors) were included in the MCC (MCC12) or not (MCC5). For 14 of those measures among adults with MCC12 (3 component chronic conditions, 2 risk factors, 4 access to health care measures, 2 disability/employment measures, and 3 quality of life measures) age group differences remained after adjustment for demographic and health measures. These included 10 measures that had similar results for adults with and without MCC12 and 4 measures (disability, being unable to work, fair or poor health and FAL) that showed significant age differences only among adults with the MCC.
Some of these age differences for adults with MCCs can be easily explained by similar differences among adults without the MCC, but the results could still be important. For example, most uninsured adults are younger than 65 years, and younger adults with MCCs were more likely than older adults to report a cost barrier to their health care in the past year. Younger adults with MCCs were also less likely to report a recent routine check-up than adults aged 65 or older with MCCs. These are all important findings in light of the continuing need to manage and treat existing chronic conditions and diagnose incident ones. This finding appears to be somewhat inconsistent with results showing that medical care expenditures for chronic conditions for adults aged 18 to 44, 45 to 64, and 65 or older with MCCs were similar at approximately $9,000 for those with 4 or more chronic conditions and approximately $4,000 for those with 2 or 3 (6). However, those data included only expenditures for those who received care for their chronic conditions, and younger adults with MCCs were less likely than older adults with similar numbers of MCCs to be treated (6). Thus, some people (eg, the uninsured, those reporting a cost barrier to care in this study) may have been unable to get needed treatment for their chronic conditions.
Quality of life measures have been studied before using BRFSS data (19), and results indicated that people with 3 or more chronic conditions and those with CVD or diabetes were more likely to report poorer quality of life than those with fewer or different chronic conditions; however, this analysis did not compare age groups. Although not directly compared, adults with MCC12 in our study appeared more likely to report poorer quality of life than adults without MCC12. Some of our study findings may result from age differences in the composition of the MCCs (eg, more depression and cognitive impairment among younger adults), which might have a greater effect on mental health compared with other chronic conditions. In particular, higher rates of depression among younger adults may be a crucial factor, because depression is the leading cause of disability worldwide (20). That fact would not fully explain results, however, because only MCC12 included depression whereas MCC5 did not, and rates of FMD were higher for both age groups among adults with MCC5 compared with adults with MCC12. Differences in reported quality of life could also result from different contexts, because younger adults were much more likely to be employed than older adults. For example, interpretation of activity limitations may depend on age, employment status, or both. However, even when controlling for measures including employment status and depression, these age differences remained for 14 measures representing a range of outcomes. These results may also reflect the direct or indirect impact of other factors such as smoking or obesity that are also higher among younger adults and may affect health and disability status. Whatever the cause of the differences, results highlight the current impact of MCCs on younger adults.
The higher rates of asthma, depression, and cognitive impairment among younger adults with MCCs were not totally unexpected. Age-related differences in MCCs using hospital discharge data indicated, for example, that among adults 18 to 44 years, the dyad of depression and substance abuse was most common (21). Our results, which lack information on substance abuse, are consistent with the earlier finding, by showing that compared with elderly adults, depression was more common among working age adults with or without MCCs. Along with depression, risk factors of obesity and smoking were also higher among younger adults with and without MCCs. Rates of hypertension, high cholesterol, and diabetes were all lower among younger adults with MCCs, but because these risk factors can also be risk factors for other chronic conditions (8–10), they may still be important. The presence of these well-recognized risk factors suggests that interventions are needed to target nonelderly adults with MCCs to reduce their risk of developing additional chronic conditions as they age.
The inclusion of cognitive impairment in the measures is consistent with lists of chronic conditions that include dementia, autism, and schizophrenia (14), or addiction, mental illnesses, cognitive impairment, and developmental disabilities (15), any of which can complicate management of co-occurring chronic conditions. A somewhat unexpected finding was the high rate of cognitive impairment among younger adults with MCCs. This rate could result from lower rates of other chronic conditions or factors such as lack of sleep, side effects of medication, or use of illicit drugs and may not be associated with future risk of dementia (9,10). Whatever the cause, being cognitively impaired may affect someone’s ability to self-manage other chronic conditions (22).
Findings from this study add to existing information on MCCs among all adults. First, results showed that despite the fact that rates of MCCs increase with age, most adults with MCCs by these definitions were younger than age 65. Second, younger adults with these MCCs were more likely to report 14 measures, including disability and poorer quality of life, than were older adults with the same MCCs. Some age differences found in this study for adults with MCCs can be explained by similar differences between the age groups among adults without the MCC, but they may still be important. Although poorer access to health care was common among all adults younger than 65, this factor could affect management and treatment of existing chronic conditions and identification of new ones. Younger adults were also more likely than older adults to report risk factors that can increase risk of developing additional chronic conditions and thus higher rates of MCCs in the future.
Limitations of this study include the use of self-reported data and the sample being limited to noninstitutionalized adults, which likely excluded many older adults with MCCs in long-term care. Some respondents may have been unaware of a diagnosis, in which case MCCs may have been underreported. Autism, hepatitis, HIV/AIDS, osteoporosis, psychotic disorders, addiction and developmental disabilities that are not measured on the BRFSS were excluded. A strength of the study was its use of data from a large population-based survey of US adults, which makes results generalizable to all states.
Findings from this study show the extent of the burden of MCCs on nonelderly adults who represent more than 60% of all adults with MCCs. Any strategies to manage and treat chronic conditions may be affected by the poorer access to health care reported by younger adults. Interventions to address the risk factors of hypertension, high cholesterol, diabetes, depression, obesity, and smoking are needed to reduce or delay the development of additional chronic conditions. Successful interventions can reduce the burden of chronic conditions and reduce present and future health care costs from MCCs.
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Acknowledgments

No financial support was received for this work.
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Author Information

Corresponding Author: Mary L. Adams, MS, MPH, On Target Health Data LLC, 247 N Stone St, West Suffield, CT 06093. Telephone: 860-370-9035. Email: madams.ontargethealthdata@gmail.com.
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References

  1. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet 2012;380(9836):37–43. CrossRef PubMed
  2. Thorpe KE, Ogden LL, Galactionova K. Chronic conditions account for rise in Medicare spending from 1987 to 2006. Health Aff (Millwood) 2010;29(4):718–24. CrossRef PubMed
  3. Centers for Medicare and Medicaid Services. Chronic conditions among Medicare beneficiaries, chartbook, 2012 edition; 2012. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Chronic-Conditions/Downloads/2012Chartbook.pdf. Accessed July 19, 2017.
  4. Lochner KA, Cox CS. Prevalence of multiple chronic conditions among Medicare beneficiaries, United States, 2010. Prev Chronic Dis 2013;10:120137. CrossRef PubMed
  5. Willadsen TG, Bebe A, Køster-Rasmussen R, Jarbøl DE, Guassora AD, Waldorff FB, et al. The role of diseases, risk factors and symptoms in the definition of multimorbidity — a systematic review. Scand J Prim Health Care 2016;34(2):112–21. CrossRef PubMed
  6. Machlin SR, Soni A. Health care expenditures for adults with multiple treated chronic conditions: estimates from the Medical Expenditure Panel Survey, 2009. Prev Chronic Dis 2013;10:120172. CrossRef PubMed
  7. Ford ES, Croft JB, Posner SF, Goodman RA, Giles WH. Co-occurrence of leading lifestyle-related chronic conditions among adults in the United States, 2002–2009. Prev Chronic Dis 2013;10:120316. CrossRef PubMed
  8. Brownson RC, Remington PL, Wegner MV. Chronic disease epidemiology and control. 3rd edition. Washington (DC): American Public Health Association; 2010.
  9. Adams ML, Grandpre J. Dose-response gradients between a composite measure of six risk factors and cognitive decline and cardiovascular disease. Prev Med 2016;91:329–34. CrossRefPubMed
  10. Baumgart M, Snyder HM, Carrillo MC, Fazio S, Kim H, Johns H. Summary of the evidence on modifiable risk factors for cognitive decline and dementia: a population-based perspective. Alzheimers Dement 2015;11(6):718–26. CrossRef PubMed
  11. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System. https://www.cdc.gov/brfss/data_documentation/index.htm. Accessed October 26, 2014.
  12. Pierannunzi C, Hu SS, Balluz L. A systematic review of publications assessing reliability and validity of the Behavioral Risk Factor Surveillance System (BRFSS), 2004–2011. BMC Med Res Methodol 2013;13(1):49. CrossRef PubMed
  13. Centers for Disease Control and Prevention. Behavioral Risk Factor Surveillance System 2013 summary data quality report; 2014. http://www.cdc.gov/brfss/annual_data/2013/pdf/2013_DQR.pdf. Accessed July 19, 2017.
  14. Goodman RA, Posner SF, Huang ES, Parekh AK, Koh HK. Defining and measuring chronic conditions: imperatives for research, policy, program, and practice. Prev Chronic Dis 2013;10:120239.CrossRef PubMed
  15. US Department of Health and Human Services. Multiple chronic conditions — a strategic framework: optimum health and quality of life for individuals with multiple chronic conditions. Washington (DC): US Department of Health and Human Services; 2010.
  16. US Census Bureau. American Community Survey (ACS). History. http://www.census.gov/people/disability/methodology/acs.html. Accessed December 21, 2016.
  17. Rabin LA, Smart CM, Crane PK, Amariglio RE, Berman LM, Boada M, et al. Subjective cognitive decline in older adults: an overview of self-report measures used across 19 international research studies. J Alzheimers Dis 2015;48(Suppl 1):S63–86. CrossRef PubMed
  18. Jessen F, Amariglio RE, van Boxtel M, Breteler M, Ceccaldi M, Chételat G, et al. ; Subjective Cognitive Decline Initiative (SCD-I) Working Group. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimers Dement 2014;10(6):844–52. CrossRef PubMed
  19. Chen H-Y, Baumgardner DJ, Rice JP. Health-related quality of life among adults with multiple chronic conditions in the United States, Behavioral Risk Factor Surveillance System, 2007. Prev Chronic Dis 2011;8(1):A09. PubMed
  20. Depression. World Health Organization; 2017. http://www.who.int/mediacentre/factsheets/fs369/en/index.html. Accessed July 19, 2017.
  21. Steiner CA, Friedman B. Hospital utilization, costs, and mortality for adults with multiple chronic conditions, Nationwide Inpatient Sample, 2009. Prev Chronic Dis 2013;10:120292.CrossRef PubMed
  22. Grober E, Hall CB, Hahn SR, Lipton RB. Memory impairment and executive dysfunction are associated with inadequately controlled diabetes in older adults. J Prim Care Community Health 2011;2(4):229–33. CrossRef PubMed