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Incidence and Prevalence of the Metabolic Syndrome Using ICD-9 and ICD-10 Diagnostic Codes, Active Component, U.S. Armed Forces, 2002–2017

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Medical Surveillance Monthly Report

Incidence and Prevalence of the Metabolic Syndrome Using ICD-9 and ICD-10 Diagnostic Codes, Active Component, U.S. Armed Forces, 2002–2017

ABSTRACT

This report uses ICD-9 and ICD-10 codes (277.7 and E88.81, respectively) for the metabolic syndrome (MetS) to summarize trends in the incidence and prevalence of this condition among active component members of the U.S. Armed Forces between 2002 and 2017. During this period, the crude overall incidence rate of MetS was 7.5 cases per 100,000 person-years (p-yrs). Compared to their respective counterparts, overall incidence rates were highest among Asian/Pacific Islanders, Air Force members, and warrant officers and were lowest among those of other/unknown race/ethnicity, Marine Corps members, and junior enlisted personnel and officers. During 2002–2017, the annual incidence rates of MetS peaked in 2009 at 11.6 cases per 100,000 p-yrs and decreased to 5.9 cases per 100,000 p-yrs in 2017. Annual prevalence rates of MetS increased steadily during the first 11 years of the surveillance period reaching a high of 38.9 per 100,000 active component service members in 2012, after which rates declined slightly to31.6 per 100,000 active component service members in 2017. Validation of ICD-9/ICD-10 diagnostic codes for MetS using the National Cholesterol Education Program Adult Treatment Panel III criteria is needed to establish the level of agreement between the two methods for identifying this condition.

WHAT ARE THE NEW FINDINGS?

This analysis confirmed that the incidence of metabolic syndrome (MetS) among service members steadily increases with advancing age. However, because the specific MetS ICD codes tend to be underutilized in patient records, this analysis' estimates of incidence greatly underestimate rates that have been derived using biologic thresholds for the five components of the syndrome.

WHAT IS THE IMPACT ON READINESS AND FORCE HEALTH PROTECTION?

MetS is a medically disqualifying condition for appointment, enlistment, or induction into military service. Significant impacts on force readiness include administrative discharges for failure to meet weight standards, non-deployability due to type 2 diabetes diagnosis requiring medication, and increased potential for cardiovascular disease in deployed environments.

BACKGROUND

The metabolic syndrome (MetS) is a cluster of cardiometabolic risk factors that is associated with increased risk of multiple chronic diseases and premature  mortality.1,2  MetS is characterized by abdominal obesity, dyslipidemia (elevated plasma triglycerides and/or reduced high density lipoprotein [HDL] cholesterol), elevated fasting plasma glucose level, and hypertension.2 The association between MetS and increased risk of multiple chronic diseases (e.g., cardiovascular disease, chronic liver disease, chronic kidney disease, arthritis, and several types of cancer) and all-cause mortality is well established.3–10 However, there is some uncertainty regarding whether MetS confers risk over and above its individual components.11,12 Regardless of whether MetS is considered to have unique predictive value, the importance of identifying and managing its individual components to decrease morbidity and mortality associated with diabetes and cardiovascular disease is undisputed.2,11,13
The importance of MetS was highlighted in 2001 with the approval of the ICD-9 code, 277.7, for “dysmetabolic syndrome X”.14 However, studies using data from the National Hospital Discharge Survey and the National Ambulatory Medical Care Survey as well as large U.S. civilian administrative databases have found that a diagnosis of MetS is rarely recorded in these data using the designated ICD code.15–18 Given this under-recording, most efforts to better estimate the public health burden of MetS in the civilian population have relied on biologic thresholds of five components of MetS (elevated waist circumference, elevated triglyceride level, reduced HDL cholesterol level, elevated blood pressure, and elevated fasting blood glucose level). These efforts have been complicated by the lack of consistency in the clinical parameters used to define MetS; however, the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPIII) criteria are one of the most widely agreed upon criteria for MetS.19 These criteria do not include the designated ICD code for MetS but define MetS by the presence of at least three of the five components based on laboratory and vital data. Studies using this definition and data from the National Health and Nutrition Examination Survey (NHANES) estimated the overall age-adjusted prevalence of MetS in 1988–1994 to be 25.3%.20  In 1999–2006, the overall age-adjusted prevalence declined slightly to 25.0%20 and then increased to 34.3% in 2007–2014.21 Examination of trendsfrom 2007 through 2014 showed that the prevalence of MetS remained relatively stable in all age, sex, and race/ethnicity groups.21
The majority of studies that have examined the prevalence of MetS among U.S. military personnel have done so among specific subpopulations (e.g., soldiers at accession, veterans with or without cardiovascular disease or diabetes mellitus, those exposed  to  environmental hazards).22–34  However, few studies have examined the prevalence of MetS among active component service members.34 Using electronic health record data from the Military Health System (MHS) Management Analysis and Reporting Tool and the NCEP-ATPIII criteria for defining MetS, Herzog et al. demonstrated a trend of decreasing prevalence of MetS among a sample of active duty service members during fiscal years 2009–2012.34 Age-adjusted MetS prevalence among male service members in the sample decreased from 24.7% in 2009 to 21.1% in 2012. The decrease in age-adjusted prevalence was not as pronounced among female service members (10.0% in 2009 to 8.3% in 2012).34
To determine and document the long term trends in diagnoses of MetS in the active component population, the current report summarizes trends in the incidence and prevalence of MetS using the ICD-9 and ICD-10 codes for this condition among active component members of the U.S. Armed Forces during 2002–2017.

METHODS

The surveillance period was January 1, 2002 through December 31, 2017. The surveillance population consisted of all individuals who served in the active component of the Army, Navy, Air Force, or Marine Corps at any time during the surveillance period. Cases of MetS were identified by ICD-9 diagnostic code 277.7 and ICD-10 code E88.81 recorded in standardized records of inpatient and outpatient encounters in military and non-military medical facilities documented in the Defense Medical Surveillance System (DMSS).
An incident case of MetS was defined by hospitalization with a case-defining diagnostic code in any diagnostic position or by two or more outpatient diagnoses between 1 and 180 days apart, with at least one of these diagnoses in a primary diagnostic position. An individual could be counted as an incident case of MetS once per lifetime. Individuals who met the case-definition for MetS prior to the surveillance period (i.e., prevalent cases) were excluded from the incidence rate calculation. Incidence rates were calculated as incident MetS diagnoses per 100,000 person years (p-yrs) of active component service. Both deployed and non-deployed person time were used in the denominator.
Lifetime prevalence of the diagnoses of MetS was estimated for each year in the 16-year surveillance period. The numerator for annual lifetime prevalence calculations consisted of service members who had ever been diagnosed with MetS and who were in service during the given calendar year. The denominator for annual prevalence calculations consisted of the total number of active component service members who served at any time during the given year. Annual prevalence estimates were calculated as the number of prevalent cases per 100,000 active component service members.

RESULTS

During 2002–2017, a total of 1,639 active component service members received incident diagnoses of MetS, for a crude overall incidence rate of 7.5 cases per 100,000 p-yrs (Table 1). The overall incidence of MetS among females was more than twice that of males (13.9 per 100,000 p-yrs and 6.4 per 100,000 p-yrs, respectively). Crude overall rates of MetS increased with increasing age; the greatest percent increase in overall incidence rates occurred between those aged 30–34 years and those aged 35–39 years or older (Table 1). Across all cases, the median age at the time of incident MetS diagnosis was 36 years (interquartile range [IQR]=30–41) with females having a much younger median age at diagnosis (31 years; IQR=26–38) compared to males (38 years; IQR=32–42) (data not shown).
Compared to their respective counterparts, overall incidence rates were highest among Asian/Pacific Islanders (9.8 per 100,000 p-years), Air Force members (9.4 per 100,000 p-yrs), and warrant officers (17.8 per 100,000 p-yrs) and lowest among those of other/unknown race/ethnicity (6.7 per 100,000 p-yrs), Marine Corps members (1.9 per 100,000 p-yrs), and junior enlisted personnel and officers (2.8 and 4.3 per 100,000 p-yrs, respectively). Stratification by military occupation revealed that crude overall rates of MetS were highest among healthcare workers (13.4 per 100,000 p-yrs) and lowest among those in combat-specific occupations (4.4 per 100,000 p-yrs) (Table 1). Of active component service members with known locations of military assignment, overall incidence of MetS was highest among those stationed in the Northeastern region of the U.S. (17.6 per 100,000 p-yrs) and lowest among those stationed overseas (2.3 per 100,000 p-yrs) or in the West (7.9 per 100,000 p-yrs). During 2002–2017, the crude annual incidence rates of MetS peaked in 2009 at 11.6 cases per 100,000 p-yrs and decreased to 5.9 cases per 100,000 p-yrs in 2017 (Figure 1). Crude annual prevalence rates of MetS increased steadily during the first 11 years of the surveillance period reaching a high of 38.9 per 100,000 active component service members in 2012, after which rates declined slightly to 31.6 per 100,000 active component service members in 2017 (Figure 2).

EDITORIAL COMMENT

The results of the current study show a trend of steadily increasing prevalence of MetS diagnoses (based on  ICD-9/ICD10 codes alone) among active component service members between 2002 and 2012 followed by a slight decline during the subsequent five years. In contrast, the findings of Herzog et al. demonstrated a decrease in MetS prevalence in a sample of active duty service members between 2009 and 2012,34 while the MetS prevalence estimates for the general U.S. population (NHANES) remained relatively stable during 2009–2014.21 However, because the estimates from the Herzog et al. and U.S. general population-based studies used different sets of modified NCEP-ATP III criteria to identify MetS cases, they are not directly comparable to those obtained in the current analysis which used only ICD-9/ICD-10 diagnostic codes. The most comparable prevalence estimate available at the time of this report was obtained from a recent study of cardiometabolic risk factors among soldiers who accessed into the U.S. Army during 2001–2011. Using the ICD-9 diagnostic code to identify MetS cases, Hruby et al. obtained a prevalence estimate of 31.2 MetS diagnoses per 100,000 Army entrants during the 11-year period.17
Despite the major differences in case definitions used in studies of the prevalence of MetS, several broad findings of the current analysis are consistent with the literature. The age-related rise in the prevalence of MetS is well established and has been attributed to the development of central obesity in middle age associated with overeating and a decline in physical activity.35,36 In contrast to the results of general population-based studies using NHANES data and the findings of Herzog and colleagues' study of MetS prevalence among a sample of active duty service members, overall rates of MetS in the current study were higher in women than in men.21,34,37 The reasons for this difference are unclear but are likely related to sex differences in the prevalence of individual MetS components in the study population.37 The pattern of lower incidence rates observed among junior enlisted and junior officers compared to those in other grades is likely highly correlated and confounded by age. In addition, the finding that overall incidence rates of MetS were lowest among Marine Corps members may be related to differences in the age and obesity distributions of the services.38,39 The decline in the prevalence of MetS during the surveillance period might be due to earlier identification of MetS and/or more aggressive management of its component conditions. Data on trends in incidence of MetS in the general U.S. population using ICD diagnostic codes (either alone or in conjunction with other diagnostic codes and/or laboratory data relevant to components of MetS) during a comparable time period were not available at the time of this report, thus precluding comparisons to the current results. This lack of comparable results is likely due, at least in part, to the under-recording of MetS using the designated ICD code in U.S. civilian administrative databases.
Whether the designated ICD code for MetS is underutilized in the MHS is unknown. However, several potential reasons for the low coding rate of MetS in the civilian health system have been posited. Some healthcare providers may think that the MetS is not a meaningful concept and thus lacks clinical utility.11,40 In addition, it is possible that lack of or limited reimbursement for MetS by some commercial insurers may lead healthcare providers to focus on using diagnostic codes that can receive reimbursement (e.g., diabetes, hypertension).41 Low frequency of coding also may be due to concern regarding the impact of the use of the MetS diagnostic code on life insurance policies and health insurance portability.42 Additionally, limited coding time during clinic appointments may be devoted to other more urgent clinical conditions.43,44
It is important to note that, because diagnostic codes from inpatient and outpatient medical records were used as proxies for incident and prevalent cases, the validity of the current results depends upon the accuracy of a physician-assigned diagnosis of MetS. Furthermore, the pattern of, and trends in, prevalence and incidence rates reported here may be due, to an unknown degree, to variations in coding practices. Validation of ICD-9/ICD-10 diagnostic codes for MetS using ATP III criteria modified for the MHS electronic health record data available (e.g., self-reported  height  and  weight) is needed to establish the level of agreement between the two methods for identifying this condition.
Another limitation of the current analysis is related to the implementation of MHS GENESIS, the new electronic health record for the Military Health System. For 2017, medical data from sites that were using MHS GENESIS are not available in DMSS. These sites include Naval Hospital Oak Harbor, Naval Hospital Bremerton, Air Force Medical Services Fairchild, and Madigan Army Medical Center. Therefore, medical encounter and person-time data for individuals seeking care at one of these facilities during 2017 were not included in the analysis.
MetS has obvious effects on accession into and retention in the military, most notably with respect to maintenance of flight status or the requirements of other special missions. Additional significant impacts of MetS on force readiness are based on administrative discharges for failure to meet weight standards, non-deployability due to type 2 diabetes diagnosis requiring medication, and increased potential for cardiovascular disease in deployed environments.45-47 Future investigations of the incidence and prevalence of MetS among active component service members should employ a fuller range of available administrative data including the diagnostic codes for the individual components of MetS, codes pertaining to the biologic thresholds for these components, and documentation of prescription medication used to treat these component conditions.

Acknowledgments: The authors thank COL Babette C. Glister (Walter Reed National Military Medical Center, Bethesda, MD) for her review of this work and valuable input into its content.

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FIGURE 1. Number of incident cases and crude incidence rates of metabolic syndrome, active component, U.S. Armed Forces, 2002–2017FIGURE 2. Number of prevalent cases and crude prevalence rates of metabolic syndrome, active component, U.S. Armed Forces, 2002–2017FIGURE 2. Number of prevalent cases and crude prevalence rates of metabolic syndrome, active component, U.S. Armed Forces, 2002–2017

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Ocular injuries present an ongoing threat to readiness and retention of service members. This report describes a new approach to categorizing ocular injury using Military Health System data, the application of an algorithm to a dataset, and the verification of the results using an audit of clinical data.

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Medical Surveillance Monthly Report

Diagnosis of hepatitis C infection and cascade of care in the active component, U.S. Armed Forces, 2020

Article
2/1/2022
Navy Petty Officer 2nd Class Cecil Dorse, left, and Navy Petty Officer 3rd Class Janet Rosas test blood samples aboard the Military Sealift Command hospital ship USNS Comfort while the ship is in New York City in support of the nation’s COVID-19 response, April 6, 2020. Photo By: Navy Petty Officer 2nd Class Sara Eshleman

Hepatitis C virus (HCV) infection rates are rising in the U.S. despite widely available tools to identify and effectively treat nearly all of these cases. This cross-sectional study aimed to use laboratory data to evaluate the prevalence of HCV diagnoses among active component U.S. military service members.

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Medical Surveillance Monthly Report

Surveillance Snapshot: Lengths of Hospital Stays for Service Members Diagnosed with Sepsis, Active Component, U.S. Armed Forces, 2011–2020

Article
1/1/2022
The (left to right) Senior Airman Austin Shrewsbury, 88th Diagnostics and Therapeutic Squadron medical laboratory technician, works with student, Airman 1st Class Taylor Altman, 88th Diagnostics and Therapeutic Squadron medical laboratory technician, to identify bacteria of patient’s cultures inside the microbiology laboratory at Wright-Patterson Air Force Base medical center June 30, 2017.

Sepsis is a serious and life-threatening organ dysfunction caused by a dysregulated host response to infection. In the U.S., sepsis is a leading cause of in-hospital mortality and 1 of the most expensive conditions treated in U.S. hospitals.

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Medical Surveillance Monthly Report

Description of a COVID-19 Beta Variant Outbreak, Joint Base Lewis-McChord, WA, February–March 2021

Article
1/1/2022
U.S. Army Soldiers from 1-17th Infantry Battalion, 2nd Stryker Brigade, 2nd Infantry Division, clear an objective during the training exercise Bayonet Focus 19-02 at Yakima Training Center, Wash., May 6, 2019. Bayonet Focus is a training exercise designed to assess Soldiers’ ability to preform tasks and complete objectives under conditions experienced during combat situations. (U.S. Army photo by Spc. Angel Ruszkiewicz)

This report describes an outbreak of SARS-CoV-2, the causative agent of COVID-19, that peaked during 21–26 February 2021 and was tied to a single military training event. A total of 143 laboratory-confirmed cases were identified.

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Medical Surveillance Monthly Report

COVID-19 and Depressive Symptoms Among Active Component U.S. Service Members, January 2019–July 2021

Article
1/1/2022
With the holiday season upon us, the cold, dark days that winter brings, and the social distancing and movement restrictions brought about by COVID-19, it’s not uncommon for people to feel depressed. (Photo by Erin Bolling)

This study examined the rates of depressive symptoms in active component U.S. service members prior to and during the COVID-19 pandemic and evaluated whether SARS-CoV-2 test results (positive or negative) were associated with self-reported depressive symptoms.

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Medical Surveillance Monthly Report
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Last Updated: January 09, 2020

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