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Keywords:

  • Arthritis;
  • Smoking;
  • Hypertension;
  • Hospitalization;
  • NHEFS;
  • NHANES

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

Objective

To compare the impact of arthritis, smoking, and residual hypertension on the annual rate of hospital admissions in adults ages 45–74, because arthritis imposes a heavy health burden on individuals and higher medical costs on the nation.

Methods

A simulation model was used to estimate annual hospital admissions attributable to each risk factor for all adults ages 45–74, and for overweight adults in that age bracket, from the Third National Health and Nutrition Examination Survey (NHANES III).

Results

Arthritis accounted for 6.2% of annual hospital admissions (8.1 admissions per 1,000 NHANES III adults). Current smoking accounted for a slightly larger share of admissions (7.0% or 9.1 admissions per 1,000 adults) and residual hypertension accounted for a smaller share (2.3% or 3.0 admissions per 1,000 adults). Because arthritis is more prevalent in overweight adults, it accounted for 7.4% of admissions (11.0 admissions per 1,000 annually in this group), compared with 5.8% for smoking (8.6 admissions per 1,000).

Conclusion

Although the impact of smoking and hypertension receives more attention from the media, the impact of arthritis on hospitalizations is substantial. This finding provides additional support for the goals of the National Arthritis Action Plan.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

Arthritis affects 17.5% of all adults, and is the leading cause of disability in the United States (1). Although it is not a fatal condition, the health burden related to arthritis is substantial. Functional and physical limitations are far greater in persons with arthritis than in those without, and having arthritis appears to exacerbate the clinical course of other chronic conditions (i.e., cancer, hypertension, and coronary heart disease) by increasing the limitation of activities of daily living (2) and the risk of cardiovascular events (3). The social impact of arthritis is also great; arthritis patients are more likely to report needing assistance from others, and report fewer opportunities for social interaction and sports or outdoor activities (4).

Arthritis is more common in overweight adults (5); a recent study found that overweight adults were 4 times more likely to have arthritis than adults of normal weight (6). Another study estimated that adults with arthritis and other rheumatic conditions accounted for approximately $186.9 billion in medical care expenditures (7). Furthermore, research has shown that hospital admissions are the largest component of rheumatoid arthritis costs, accounting for more than 50% of the annual cost of rheumatoid arthritis (8, 9).

We compared the impact of arthritis on the number of hospitalizations of adults ages 45–74 with the impact attributable to smoking and hypertension. A simulation model based on the National Health and Nutrition Examination Survey I (NHANES I) Epidemiologic Followup Study (NHEFS) was used to estimate the hospital admissions attributable to each risk factor in NHANES III adults ages 45–74. Several features of the model helped ensure that the estimates were comparable. First, the model estimates hospital admissions for any cause, which reflect the effect of each risk factor on admissions for which it is either the principal cause, or a contributing cause. Second, the equations that link risk factors to admissions are based on a single, population-based nationally-representative dataset. Third, a wide range of risk factors is included in the model, so that the effect of each is estimated after controlling for all others.

SUBJECTS AND METHODS

The National Health and Nutrition Examination Surveys (NHANES) are large national surveys conducted by the National Center for Health Statistics that collect information about risk factors and health outcomes of representative samples of Americans. The NHANES are the basis for national studies and goals, such as some of those in Healthy People 2010, a national health report designed to identify significant preventable threats to health and to establish national goals to reduce these threats (10).

The estimates presented in this article are based on data from the NHANES I and NHANES III. The NHANES I, fielded in 1971–1975, is unique in that it had a longitudinal followup, (NHANES I Epidemiologic Followup Study [NHEFS]), which tracked participants' health for 2 decades, allowing baseline risk factors to be linked to subsequent outcomes. The NHEFS was used as the basis for our simulation model. The hospitalization submodel of the simulation model was applied to data for adults from NHANES III, fielded in 1988–1994, because the prevalence of risk factors in that survey better represents current trends in adults (e.g., more obesity, and fewer smokers).

Hospitalization submodel

The hospitalization submodel consists of projection equations based on the NHEFS that link annual hospital admissions for each person to a comprehensive set of risk factors measured at baseline. The submodel subdivides men and women ages 45–74 into 4 groups (men ages 45–64 and 65–74 and women 45–64 and 65–74), and uses separate regressions for each group. The NHEFS excluded persons older than 74 at baseline. For each person (i) within an age-sex group in each year of followup (t), logged hospital admissions during the year were related to the individual's baseline characteristics using the following equation:

Ln admissionsit = f (risk factors)

where risk factors equal arthritis, current smoking, former smoking, ln systolic blood pressure, overweight, or other risk factors discussed below. The equations are negative binomial count regressions fitted with STATA statistical software, version 3.1 (Stata Corporation, College Station, TX), (regressions available on request from the author). Count regressions are closely related to hazard models. They model the number of events during a period of time (in this study, a year), while hazard models focus on the duration of time between events. Count models are particularly appropriate for data such as annual hospital admissions because they are built on probability distributions that assume that the dependent variable takes on only integer values and that zeroes and low numbers are common (11). The negative binomial is more flexible than the other commonly used count model, the Poisson, because it does not require the mean and variance of the dependent variable to be equal; it contains the Poisson as a special case. Estimates based on the hospitalization submodel have been published in 2 previous reports (12, 13).

The submodel is fitted to data for the full 2 decades of followup and can project admissions over this period, adjusting for mortality. The estimates presented here do not use the ability of the submodel to project events over time. All estimates were made for the baseline period, before anyone had died. Thus the estimates refer to the full NHANES III population in the baseline years, 1988–1994, and compare alternative scenarios for that period.

The literature on determinants of heart disease, cancer, and stroke was reviewed to identify the risk factors used in the regressions. The focus was on clinical risk factors, specifically, those that would be determined during a visit to a physician. Hospital admissions were related to all clinical risk factors that have been shown to be statistically significantly related to disease and/or death in multiple studies: age, race, smoking, systolic blood pressure, overweight and underweight, laboratory test results (serum albumin, serum cholesterol), exercise, alcohol consumption, diet (fiber, fish/shellfish, fruits/vegetables), and 9 groups of chronic conditions (12, 14, 15). The effect of each risk factor, including arthritis, smoking, and blood pressure, was estimated after controlling for all other risk factors. The measurement of the 3 risk factors focused on in the study (arthritis, current smoking, and hypertension) is described below (12, 14, 15).

A dichotomous variable for arthritis was defined, based on each participant's answer to the question in the NHANES I medical history interview, “Has a doctor ever told you that you have had arthritis?” Because the question did not distinguish between osteoarthritis and rheumatoid arthritis, the answer encompassed both.

Only half of NHANES I participants were asked about their smoking habits at baseline; however, at the first NHEFS followup in 1982–1984, the National Center for Health Statistics retrospectively collected this information for the other half of the participants. Retrospective information was used only when baseline information was missing. Machlin et al (16) reported that, for participants ages 45–74 with both baseline and retrospective data, and for the 3 categories of smokers used here (current, former, never), the 2 sources matched for 89% of subject respondents and 83% of proxy respondents (proxies were used primarily for people who had died). Smoking was represented by 2 dichotomous variables in the regressions, one for participants who were smokers at baseline, and one for participants who reported being former smokers. Never smokers were the comparison group.

Participants' systolic blood pressure was measured only once during their physical examinations. Because a single measurement can be atypical, national guidelines recommend that a diagnosis of hypertension be based on several measurements taken at different visits (17). However, because the NHEFS is longitudinal (individuals were followed for 2 decades after baseline and hospitalizations were recorded), our estimating equations self-correct for this problem. Individuals who had an unusually high single baseline pressure measurement would naturally have had the number of hospitalizations during followup that corresponded to their true lower pressures. The equations linking hospitalizations to baseline pressures thus correct for regression to the mean because persons whose pressures were overstated by a single reading contributed a smaller number of hospitalizations during followup than those with genuinely elevated pressures. Systolic blood pressure was a continuous variable in the estimating equations. All continuous risk factors were entered in log form because logs gave a better fit.

The equations used in this analysis, and those used in the study by Russell et al (13), were based on the full NHEFS followup through 1992. These equations project the sample experience well, tracking both the higher admissions of the 1970s and early 1980s, and the drop in admissions due to managed care in the later 1980s and early 1990s (18). Although the model's projections for 1988–1992 exceeded observed admissions, data from the benchmark National Hospital Discharge Survey showed that they accurately represented the longer-term trends beyond the early 1990s, especially the return to rising annual admission rates among people ages 65 and older (19).

Cohort dataset

The hospitalization submodel was used to estimate the impact of arthritis, smoking, and hypertension on the number of hospital admissions in adults ages 45–74 in the NHANES III. The cohort dataset includes all NHANES III respondents in this age group who were examined by a physician (n = 6,265). Data were used on all sample persons because 84% of the respondents had complete information available, 9% of the respondents had missing data for only one risk factor, and only 0.21% (13 individuals) were missing data for more than 5 risk factors. Missing values were replaced with the mean of the risk factor for the age-sex group.

Arthritis, smoking habit, and systolic blood pressure were determined in the same manner in both the NHANES I and NHANES III (except that all NHANES III adults were asked about smoking at baseline). Because the NHANES I measured systolic pressure only once (see above), the first NHANES III measurement was used in the analysis to maintain consistency with the projection equations.

Sample weights

NHANES III was a stratified cluster sample. Our estimates for each sample person were weighted to reflect his/her share of the US population of noninstitutionalized adults in 1988–1994. Of several statistical weights available for NHANES III, we used the weight associated with medical examinations.

Estimates

Baseline estimates of annual hospital admission rates were calculated by entering observed baseline values of the risk factors for the 6,265 NHANES III adult respondents ages 45–74 into the model equations, and calculating admissions for the baseline period. Population attributable-risk estimates were then calculated for 3 scenarios. In each scenario, 1 risk factor was changed in the baseline period, while all other risk factors remained at observed baseline values. These scenarios followed the standard definition of population attributable risk, which measures the amount of the health problem that could have been prevented if the risk factor had never existed (20). The differences between the baseline estimates and each of the attributable-risk estimates represent number of hospital admissions attributable to arthritis, current smoking, and hypertension, respectively. Simulations were run separately for all persons ages 45–74 and overweight persons ages 45–74. The scenarios are described in detail below, and the same procedures were followed for both groups.

Attributable risk scenarios

Arthritis eliminated. All NHANES III adults ages 45–74 with arthritis were identified, and the dichotomous variable representing arthritis was set equal to 0 for them (no arthritis); it was already 0 for other adults. The model was run with the new values for arthritis while all other risk factors, including smoking and systolic blood pressure, remained at baseline values.

Current smoking eliminated

All current smokers at baseline were identified, and the dichotomous variable representing current smoking was set to zero for them. Former smokers remained former smokers and both smoking variables remained at zero for true nonsmokers. The model was run with the new values for current smoking while all other risk factors, including arthritis and systolic blood pressure, remained at baseline values.

Hypertension eliminated

All persons with systolic pressures of 140 mm Hg or higher (the category that defines hypertension) were identified and their pressures were reduced to 139. Pressures of other adults remained at their observed baseline levels. It is important to note that by 1988–1994 when NHANES III was conducted, hypertension was often treated aggressively and some NHANES III adults had successfully reduced their systolic pressures to below 140 mm Hg. Others, although still hypertensive, had reduced their pressures below what they would have been naturally. For these reasons, the estimates for hypertension are best described as showing the effects of “residual” hypertension; these estimates have been published previously (13).

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

In 1988–1994, each of the 3 risk factors (arthritis, current smoking, and residual hypertension) was common in NHANES III adults ages 45–74 (Table 1). Approximately 33.5% of the sample reported having arthritis, 24.0% of the sample were current smokers, and 27.8% had residual hypertension. A substantial percentage of the sample was overweight (43.3%). Men were more likely to be current smokers and women were more likely to have arthritis. Both arthritis (41.0%) and residual hypertension (33.6%) were more prevalent in the overweight sample.

Table 1. Percentages of adults ages 45–74 from the Third National Health and Nutrition Examination Survey (NHANES III) with arthritis, current smoking habit, and residual hypertension*
 ArthritisCurrent smokerResidual hypertensionOverweight
  • *

    Weighted to represent all non-institutionalized US adults in 1988–1994.

  • Residual hypertension defined as systolic blood pressure 140 mm Hg or higher. The term residual hypertension recognizes that pressures of many adults had been reduced by treatment, even though not <140 mm Hg.

All adults    
 Men28.727.129.841.1
 Women37.821.326.145.2
 Total33.524.027.843.3
Overweight adults    
 Men37.021.635.0100
 Women44.318.332.4100
 Total41.019.833.6100

Estimates for all persons ages 45–74

Arthritis had a substantial effect on the number of hospital admissions: when arthritis was eliminated at baseline, the annual hospital admission rate was reduced by 6.2%, or 8.1 admissions per 1,000 (Table 2). Eliminating smoking had the largest effect on the number of hospital admissions. If all current smokers had been nonsmokers at baseline, the annual hospital admission rate would have been reduced by 7.0%, or 9.1 admissions per 1,000. Residual hypertension had the smallest effect on hospital admissions; its elimination was associated with a reduction of 2.3% or 3.0 fewer admissions per 1,000.

Table 2. Annual hospital admissions per 1,000 persons for all adults ages 45–74, at baseline and after elimination of risk factors
Risk factor eliminatedMenWomenTotal
RateAbsolute change% changeRateAbsolute change% changeRateAbsolute change% change
  • *

    Baseline refers to estimates based on the observed prevalence of all risk factors in the Third National Health and Nutrition Examination Survey (NHANES III).

  • Residual hypertension defined as systolic blood pressure 140 mm Hg or higher. The term residual hypertension recognizes that pressures of many adults had been reduced by treatment, even though not <140 mm Hg.

Baseline*136.5  124.4  130.1  
Arthritis128.9−7.6−5.6115.8−8.6−6.9122.0−8.1−6.2
Current smoking122.3−14.2−10.4119.9−4.5−3.7121.0−9.1−7.0
Residual hypertension133.8−2.7−2.0121.1−3.3−2.6127.1−3.0−2.3

The role of current smoking on the rate of hospital admissions varied by sex. The impact of eliminating current smoking was almost 3 times greater in men (a reduction of 10.4%, or 14.2 fewer admissions per 1,000) than in women (a reduction of 3.7%, or 4.5 fewer admissions per 1,000 annually). The effects of arthritis and residual hypertension did not vary by sex.

Estimates for overweight persons ages 45–74

At baseline and for each population attributable-risk scenario, annual hospital admission rates for the overweight sample exceeded those for all adults ages 45–74 (Table 3). Elimination of arthritis and smoking had comparable effects. Eliminating arthritis in overweight adults reduced hospital admission rates at baseline by 7.4% (11.0 fewer admissions per 1,000 overweight adults), while eliminating current smoking was associated with a 5.8% reduction in annual hospital admission rates (8.6 fewer admissions per 1,000 overweight adults). The elimination of residual hypertension resulted in a reduction of only 2.7% in hospital admissions (4.0 fewer hospital admissions per 1,000 overweight adults).

Table 3. Annual hospital admissions per 1,000 persons for overweight adults ages 45–74, at baseline and after elimination of risk factors
Risk factor eliminatedMenWomenTotal
RateAbsolute change% changeRateAbsolute change% changeRateAbsolute change% change
  • *

    Baseline refers to estimates based on the observed prevalence of all risk factors in the Third National Health and Nutrition Examination Survey (NHANES III).

  • Residual hypertension defined as systolic blood pressure 140 mm Hg or higher. The term residual hypertension recognizes that pressures of many adults had been reduced by treatment, even though not <140 mm Hg.

Baseline*159.0  140.2  148.7  
Arthritis148.5−10.6−6.7128.8−11.4−8.1137.6−11.0−7.4
Current smoking145.6−13.5−8.5135.6−4.6−3.3140.1−8.6−5.8
Residual hypertension155.5−3.6−2.3135.9−4.3−3.0144.7−4.0−2.7

Figure 1 compares the reductions in hospital admissions due to arthritis, current smoking, and residual hypertension for all adults and for overweight adults. Of the 3 risk factors studied, arthritis was the most important contributor to annual hospital admissions for overweight adults ages 45–74, while current smoking was the most important contributor for all adults.

thumbnail image

Figure 1. Hospital Admissions per 1,000 for all adults and overweight adults ages 45–74, after elimination of arthritis, current smoking, and hypertension. Values are percentage changes in annual rates.

Download figure to PowerPoint

In the overweight sample as in the full sample, the impact of eliminating current smoking in men was more than twice the impact in women, and the impact of eliminating arthritis and hypertension did not vary by sex.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

The results of this study help establish the fact that arthritis has a substantial impact on the number of hospital admissions. Although the estimates of hospitalizations attributable to arthritis for all adults are somewhat less than those attributable to smoking, they are substantial and exceed estimates for residual hypertension. Both smoking and hypertension receive more media attention as health risks, perhaps because of their clear impact on mortality.

For all adults ages 45–74 in the NHANES III, eliminating current smoking was associated with a 7.0% reduction in the number of hospitalizations at baseline, while the elimination of arthritis resulted in a 6.2% reduction. The effect of arthritis on hospitalizations in overweight adults exceeded the effect of current smoking (7.4% and 5.8%, respectively). Because arthritis is more common and more devastating in this group, this finding suggests a need for more targeted prevention and disease management efforts for overweight adults with arthritis.

A recently published cost-of-illness study comparing osteoarthritis, rheumatoid arthritis, and hypertension reported findings similar to ours (21). Taking into consideration both direct costs (physician visits, hospitalizations, tests, drugs) and indirect costs (time, lost productivity), this study found that the total annual cost of rheumatoid arthritis exceeded that of hypertension by more than twofold. The total annual cost of osteoarthritis was also considerably larger than that of hypertension (21). These findings further underscore the impact of arthritis on health care utilization and medical costs.

One study appears to conflict with our results. Verbrugge and Patrick, in a study that used national surveys to examine the impact of 7 chronic conditions on health care utilization, concluded that arthritis did not have a significant impact on hospital use (22). Although their results showed that arthritis was the most common chronic condition for adults over the age of 65, and ranked first for limitations in adults ages 45 years and older, the authors concluded that arthritis was not a major factor in the number of physician visits or hospitalizations. This finding is possible because in their study only principal diagnoses for office visits and hospitalizations were considered, which would tend to underestimate the role of arthritis (often as a secondary condition) in determining health care utilization. Our estimates include the effect of each risk factor as a contributing cause to hospitalizations that may carry some other primary diagnosis.

Dunlop et al acknowledged that “Regardless of the definition or the accounting method, the economic impact of arthritis is substantial and rising” (23). In 1997, arthritis and other rheumatic conditions were associated with 744,000 hospitalizations and 44 million ambulatory care visits (24). There is consistent evidence that people with arthritis experience higher medical costs than those without arthritis (23, 25). In another study, Dunlop et al demonstrated that people with arthritis were more likely to have a physician's visit, hospital admission, and out-of-pocket costs exceeding $5,000 in the previous year, after controlling for age, sex, comorbid conditions, socioeconomic status, and other demographic factors (26).

There have been a number of recent policy initiatives that address the impact of arthritis as a public health problem. Healthy People 2010 contains 8 objectives aimed at reducing the societal and personal impact of arthritis (10). In addition, the Centers for Disease Control and Prevention, in collaboration with the Arthritis Foundation and the Association of State and Territorial Health Officials, created the National Arthritis Action Plan (NAAP) (27). The NAAP is comprised of 4 goals: 1) to establish the scientific base of knowledge regarding the prevention of arthritis and disability; 2) to increase awareness of the impact of arthritis and the importance of early diagnosis, management, and prevention; 3) to implement effective prevention programs; and 4) to achieve the arthritis-related objectives outlined in the Healthy People 2010 initiative. These goals are a promising step towards alleviating both the personal and societal disease and disability burdens of arthritis, including the burden of hospitalization.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES
  • 1
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