Abstract
Background
Diabetes mellitus (DM) is common among older adults hospitalized with influenza, yet data are limited on the impact of DM on risk of severe influenza-associated outcomes.
Methods
We included adults aged ≥65 years hospitalized with influenza during 2012–2013 through 2016–2017 from the Influenza Hospitalization Surveillance Network (FluSurv-NET), a population-based surveillance system for laboratory-confirmed influenza-associated hospitalizations conducted in defined counties within 13 states. We calculated population denominators using the Centers for Medicare and Medicaid Services county-specific DM prevalence estimates and National Center for Health Statistics population data. We present pooled rates and rate ratios (RRs) of intensive care unit (ICU) admission, pneumonia diagnosis, mechanical ventilation, and in-hospital death for persons with and without DM. We estimated RRs and 95% confidence intervals (CIs) using meta-analysis with site as a random effect in order to control for site differences in the estimates.
Results
Of 31 934 hospitalized adults included in the analysis, 34% had DM. Compared to those without DM, adults with DM had higher rates of influenza-associated hospitalization (RR, 1.57 [95% CI, 1.43–1.72]), ICU admission (RR, 1.84 [95% CI, 1.67–2.04]), pneumonia (RR, 1.57 [95% CI, 1.42–1.73]), mechanical ventilation (RR, 1.95 [95% CI, 1.74–2.20]), and in-hospital death (RR, 1.48 [95% CI, 1.23–1.80]).
Conclusions
Older adults with DM have higher rates of severe influenza-associated outcomes compared to those without DM. These findings reinforce the importance of preventing influenza virus infections through annual vaccination, and early treatment of influenza illness with antivirals in older adults with DM.
Keywords: diabetes mellitus, influenza, influenza hospitalization, severe influenza outcomes
In each of the 2012–2013 through 2016–2017 influenza seasons, the rate of influenza-associated hospitalization, intensive care unit admission, pneumonia, and mechanical ventilation was consistently higher among those with diabetes mellitus (DM) than those without DM.
In most years in the United States (US), millions of people are infected with influenza virus [1, 2]. While most people experience minor symptoms following influenza virus infection, some develop severe illness, leading to hospitalization, intensive care unit (ICU) admissions, mechanical ventilation, and even death [3–6]. Influenza-associated hospitalizations are more common in older adults [5, 7] and people with certain chronic medical conditions [8–10].
Data from a national cross-sectional survey showed that 23 million US adults, and about 21% of adults aged ≥65 years, live with diabetes mellitus (DM) [11]. DM is a common comorbidity among patients hospitalized with influenza [9, 12, 13]. Understanding the impact of DM on rates of severe influenza-associated outcomes is important for informing preventive strategies, including influenza vaccination and early diagnosis and treatment of influenza with approved antivirals for people with DM. However, studies investigating the relationship between DM and risk of influenza and severe outcomes have shown mixed results. While some studies reported increased risk of severe influenza-associated outcomes among people with DM [14–17], others did not find an association [12, 18].
Additionally, population-level estimates of rates of severe influenza-associated outcomes among people with DM are limited both in the US and globally. The aim of this analysis was to estimate rates and relative risk of influenza-associated hospitalization, pneumonia, ICU admission, mechanical ventilation, and in-hospital death among adults aged ≥65 years with and without DM in the US during the 2012–2013 through 2016–2017 influenza seasons.
METHODS
Data Sources
Influenza Hospitalization Surveillance Network.
We used data from the Centers for Disease Control and Prevention’s (CDC) Influenza Hospitalization Surveillance Network (FluSurv-NET) collected during the 2012–2013 through 2016–2017 influenza seasons. Detailed descriptions of the FluSurv-NET surveillance system are published elsewhere [19, 20]. In brief, FluSurv-NET conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations in select counties in 13 states, representing approximately 9% of the US population. The FluSurv-NET catchment population is similar to the US population in age, sex, and race/ethnicity distribution. During the 2012–2013 through 2016–2017 influenza seasons, 14 FluSurv-NET sites comprising 77 counties within California, Colorado, Connecticut, Georgia, Maryland, Michigan, Minnesota, New Mexico, New York (2 sites), Ohio, Oregon, Tennessee, and Utah participated in FluSurv-NET surveillance. For this analysis, we included patients who were aged ≥65 years at the time of the influenza-associated hospitalization.
We identified hospitalized patients with laboratory-confirmed influenza through active review of notifiable disease databases and hospital and laboratory records, including laboratory logs of diagnostic testing for influenza, patient medical records, and infection control logs. We included patients who were residents of the FluSurv-NET surveillance catchment area who were hospitalized during 1 October–30 April of each season and had a positive influenza test no more than 14 days prior to admission or during hospitalization. For this analysis, we excluded patients with possible hospital-acquired influenza, defined as a positive influenza test ≥3 days after hospital admission. Laboratory testing for influenza was performed at the discretion of healthcare providers or based on facility testing policies, and laboratory confirmation was defined by a positive influenza test result using any of the following methods: rapid antigen testing, real-time reverse transcription polymerase chain reaction, viral culture, and direct or indirect fluorescent antibody staining.
Trained surveillance staff used a standardized case report form to conduct medical chart abstractions for identified patients. DM status for each patient was obtained through review of problem lists and history and physical examination notes from hospital medical records. FluSurv-NET does not collect information on indicators of DM control such as hemoglobin A1C or medications used to treat DM; thus, these data were not available for the current analysis. Data on patient demographics, smoking status, chronic underlying medical conditions, influenza vaccination status, community-acquired pneumonia, and in-hospital outcomes (ICU admissions, mechanical ventilation, and in-hospital death) were also abstracted. Pneumonia was defined as evidence of air space opacity, consolidation, lobar infiltrate, or pleural effusion in a chest radiograph taken during the first 3 days of hospital admission, and either a documentation of pneumonia on the discharge summary or a discharge diagnosis of pneumonia based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) or International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes (481–487, 510, 513, or 997.31).
The CDC determined that this activity met the requirement for public health surveillance; therefore, CDC Institutional Review Board (IRB) approval was not required. FluSurv-NET sites obtained human subjects and ethics approvals from their respective state health departments and academic partner IRBs as needed. The requirement for informed consent was waived per 45 Code of Federal Regulation part 46.
Centers for Medicare and Medicaid Services.
We used data from the Centers for Medicare and Medicaid Services (CMS) to obtain estimates of the proportion of adults aged ≥65 years with and without DM in each FluSurv-NET county. CMS reports county-level prevalence of selected chronic conditions by age group on an annual basis. Data used for the prevalence estimates were obtained from CMS administrative enrollment and claims data from the Medicare fee-for-service program [21]. If the claims data indicated that a beneficiary was treated for a specific chronic condition, CMS considered the beneficiary to be living with that chronic condition when calculating the prevalence of the chronic condition in the population. CMS used ICD-CM codes recorded in the claims data to classify beneficiary conditions. For all claims for services that occurred before 1 October 2015, CMS used ICD-9-CM for the classification and ICD-10-CM was used thereafter. (See Supplementary Appendix A for specific ICD-9-CM and ICD-10-CM codes that CMS used to define DM.) County-specific prevalence of DM was obtained by dividing the total number of beneficiaries in the county with DM by the total number of beneficiaries in the fee-for-service population in the county.
Statistical Analysis
Among patients hospitalized with influenza, we calculated frequencies and percentages of demographic characteristics, underlying medical conditions, current influenza vaccination status, antiviral treatment, and in-hospital outcomes by DM status.
To estimate the rate of each influenza-associated outcome (hospitalization, ICU admission, mechanical ventilation, pneumonia, and in-hospital death) by DM status, we first calculated the respective denominator populations using prevalence data from CMS and the National Center for Health Statistics’ (NCHS) vintage bridged-race postcensal population estimates for the counties included in FluSurv-NET surveillance. We multiplied the CMS-estimated proportion of adults aged ≥65 years with and without DM in each FluSurv-NET county by the NCHS-estimated population of adults aged ≥65 years residing in that county during each season to obtain the yearly number of adults aged ≥65 years with and without DM in the FluSurv-NET catchment counties.
We summed the estimated population denominators for the participating counties within each site in a given season to obtain denominators by site for each season. We calculated the rate of each influenza-associated outcome by dividing the number of hospitalized FluSurv-NET patients with each outcome by the calculated catchment population of each FluSurv-NET site in a given season to obtain site-specific rates for each season. Rates were calculated for persons with and without DM. Rate ratios (among those with DM vs without DM) were calculated for each site per season by dividing the calculated rates in those with DM by rates in those without DM for each of the 5 influenza-associated outcomes. All rates and rate ratios were unadjusted for potential confounders such as age, race/ethnicity, sex, additional comorbidities, and vaccination status because these data were not available at the population level through CMS for adults with and without DM.
To account for FluSurv-NET site differences in the aggregated data, we used random effects meta-analysis models to pool the calculated rates and rate ratios for each outcome for all seasons combined and for each season individually, controlling for FluSurv-NET sites. The random-effects models were implemented in R (version 3.6.0) using the Metafor function [22]. All other analyses were conducted using SAS version 9.4 (SAS Institute, Cary, North Carolina). We report rates and rate ratios and associated 95% confidence intervals (CIs) by season and for the 5 seasons combined.
RESULTS
A total of 31 934 adults aged ≥65 years hospitalized with laboratory-confirmed influenza during the 2012–2013 through 2016–2017 influenza seasons were included in this analysis. The median age was 80 years (interquartile range, 72–87 years), 55.4% were female, 68.7% were White, and 94.2% had 1 or more underlying conditions (Table 1). In total, 10 863 (34%) had DM. Antiviral treatment was prescribed for 88% and 87% of the patients with DM and without DM, respectively. The proportions with select underlying conditions and vaccination status among patients with and without DM (respectively) are as follows: cardiovascular disease (68.5% vs 57.6%), renal disease (35.6% vs 19.9%), obesity/extreme obesity (41.7% vs 22%), and receipt of current season influenza vaccine (58.4% vs 56.1%).
Table 1.
Demographic and Clinical Characteristics of Adults ≥65 Years of Age Hospitalized With Influenza, With and Without Diabetes Mellitus—Influenza Hospitalization Surveillance Network (FluSurv-NET), 2012–2017
| Variable | Total (N = 31 934) | Adults With DM (n = 10 863) | Adults Without DM (n = 21 071) |
|---|---|---|---|
| Sex | |||
| Male | 14 253 (44.6) | 5232 (48.2) | 9021 (42.8) |
| Female | 17 681 (55.4) | 5631 (51.8) | 12 050 (57.2) |
| Age, y | |||
| Median (IQR) | 80 (72–87) | 78 (71–84) | 81 (73–88) |
| 65–74 | 10 174 (31.9) | 4185 (38.5) | 5989 (28.4) |
| 75–84 | 11 107 (34.8) | 4036 (37.2) | 7071 (33.6) |
| ≥85 | 10 653 (33.4) | 2642 (24.3) | 8011 (38) |
| Race/ethnicity | |||
| Non-Hispanic White | 21 939 (68.7) | 6638 (61.1) | 15 301 (72.6) |
| Non-Hispanic Black | 3508 (11) | 1656 (15.2) | 1852 (8.8) |
| Non-Hispanic American Indian/Alaska Native | 110 (0.3) | 51 (0.5) | 59 (0.3) |
| Non-Hispanic Asian/Pacific Islander | 1719 (5.4) | 746 (6.9) | 973 (4.6) |
| Non-Hispanic multiracial | 26 (0.1) | 11 (0.1) | 15 (0.1) |
| Hispanic/Latino | 1634 (5.1) | 803 (7.4) | 831 (3.9) |
| Unknown | 2998 (9.4) | 958 (8.8) | 2040 (9.7) |
| Smoking status | |||
| Current smoker | 3252 (10.2) | 992 (9.1) | 2260 (10.7) |
| Former smoker | 12 274 (38.4) | 4341 (40) | 7933 (37.7) |
| Never smoker/unknown | 16 408 (51.4) | 5530 (50.9) | 10 878 (51.6) |
| Vaccination in the current seasona | |||
| No | 9861 (30.9) | 3303 (30.4) | 6558 (31.1) |
| Yes | 18 156 (56.9) | 6339 (58.4) | 11 817 (56.1) |
| Unknown | 3917 (12.3) | 1221 (11.2) | 2696 (12.8) |
| Antiviral treatmentb | |||
| No | 3705 (11.6) | 1238 (11.4) | 2467 (11.7) |
| Yes | 28 028 (87.8) | 9600 (88.4) | 18 428 (87.5) |
| Unknown | 201 (0.6) | 25 (0.2) | 176 (0.8) |
| Any underlying medical condition (including DM) | |||
| No | 1641 (5.1) | … | 1641 (7.8) |
| Yes | 30 074 (94.2) | 10 863 (100) | 19 211 (91.2) |
| Unknown | 219 (0.7) | … | 219 (1) |
| Cardiovascular disease | |||
| No | 12 351 (38.7) | 3424 (31.5) | 8927 (42.4) |
| Yes | 19 583 (61.3) | 7439 (68.5) | 12 144 (57.6) |
| Renal disease | |||
| No | 23 866 (74.7) | 6997 (64.4) | 16 869 (80.1) |
| Yes | 8068 (25.3) | 3866 (35.6) | 4202 (19.9) |
| Chronic lung disease | |||
| No | 21 482 (67.3) | 7455 (68.6) | 14 027 (66.6) |
| Yes | 10 452 (32.7) | 3408 (31.4) | 7044 (33.4) |
| Neurologic/neuromuscular disease | |||
| No | 22 195 (69.5) | 7712 (71) | 14 483 (68.7) |
| Yes | 9739 (30.5) | 3151 (29) | 6588 (31.3) |
| Immunosuppression | |||
| No | 27 315 (85.5) | 9382 (86.4) | 17 933 (85.1) |
| Yes | 4619 (14.5) | 1481 (13.6) | 3138 (14.9) |
| Classification of weight status | |||
| Underweight | 1420 (4.5) | 230 (2.1) | 1190 (5.7) |
| Normal/healthy | 10 093 (31.6) | 2327 (21.4) | 7766 (36.9) |
| Overweight | 9426 (29.5) | 3223 (29.7) | 6203 (29.4) |
| Obese | 7366 (23.1) | 3452 (31.8) | 3914 (18.6) |
| Morbidly obese | 1794 (5.6) | 1076 (9.9) | 718 (3.4) |
| Unknown | 1835 (5.8) | 555 (5.1) | 1280 (6.1) |
| Intensive care unit admission | |||
| No | 27 250 (85.3) | 9136 (84.1) | 18 114 (86) |
| Yes | 4488 (14.1) | 1701 (15.7) | 2787 (13.2) |
| Unknown | 196 (0.6) | 26 (0.2) | 170 (0.8) |
| Developed pneumonia | |||
| No | 24 541 (76.9) | 8378 (77.1) | 16 163 (76.7) |
| Yes | 7393 (23.2) | 2485 (22.9) | 4908 (23.3) |
| Received mechanical ventilation | |||
| No | 29 999 (93.9) | 10 159 (93.5) | 19 840 (94.2) |
| Yes | 1700 (5.3) | 664 (6.1) | 1036 (4.9) |
| Unknown | 235 (0.7) | 40 (0.4) | 195 (0.9) |
| Outcome of hospitalization | |||
| Died | 1206 (3.8) | 387 (3.6) | 819 (3.9) |
| Discharged | 30 609 (95.9) | 10 472 (96.4) | 20 137 (95.6) |
| Unknown | 119 (0.4) | 4 (0) | 115 (0.6) |
| Influenza season | |||
| 2012–2013 | 5525 (17.3) | 1828 (16.8) | 3697 (17.6) |
| 2013–2014 | 2771 (8.7) | 1011 (9.3) | 1760 (8.4) |
| 2014–2015 | 10 534 (33) | 3496 (32.2) | 7038 (33.4) |
| 2015–2016 | 2988 (9.4) | 1087 (10) | 1901 (9) |
| 2016–2017 | 10 116 (31.7) | 3441 (31.7) | 6675 (31.7) |
| Site | |||
| California | 4192 (13.1) | 1506 (13.9) | 2686 (12.8) |
| Colorado | 3009 (9.4) | 851 (7.8) | 2158 (10.2) |
| Connecticut | 2611 (8.2) | 811 (7.5) | 1800 (8.5) |
| Georgia | 2129 (6.7) | 742 (6.8) | 1387 (6.6) |
| Maryland | 3518 (11) | 1283 (11.8) | 2235 (10.6) |
| Michigan | 807 (2.5) | 286 (2.6) | 521 (2.5) |
| Minnesota | 3955 (12.4) | 1224 (11.3) | 2731 (13) |
| New Mexico | 952 (3) | 335 (3.1) | 617 (2.9) |
| New York | 4109 (12.9) | 1397 (12.9) | 2712 (12.9) |
| Ohio | 1869 (5.9) | 758 (7) | 1111 (5.3) |
| Oregon | 2181 (6.8) | 780 (7.2) | 1401 (6.7) |
| Tennessee | 1474 (4.6) | 500 (4.6) | 974 (4.6) |
| Utah | 1128 (3.5) | 390 (3.6) | 738 (3.5) |
Data are presented as No. (%) unless otherwise indicated. The χ2 test P values comparing those with and without DM were all <.01 except for pneumonia (P = .40).
Abbreviations: DM, diabetes mellitus; IQR, interquartile range.
Received current season influenza vaccine at least 2 weeks prior to hospitalization. Influenza Hospitalization Surveillance Network (FluSurv-NET), 2012–2013 through 2016–2017.
This includes treatment with oseltamivir (Tamiflu), zanamivir (Relenza), or peramivir (Rapivab).
Controlling for site differences, the pooled influenza-associated hospitalization rate per 100 000 person-years from 2012–2013 through 2016–2017 was 276 (95% CI, 230–330) in those with DM and 181 (95% CI, 150–217) in those without DM (Table 2). From 2012–2013 through 2016–2017, the pooled rates per 100 000 person-years of each of the other influenza-associated outcomes among those with and without DM, respectively, were as follows: ICU admission, 42 vs 23; pneumonia, 64 vs 42; mechanical ventilation, 17 vs 9; and in-hospital death, 11 vs 7.
Table 2.
Rates of Hospitalization, Intensive Care Unit Admission, Pneumonia, Mechanical Ventilation, and In-Hospital Death Among Adults With and Without Diabetes Mellitus—Influenza Hospitalization Surveillance Network (FluSurv-NET) and Centers for Medicare and Medicaid Services, 2012–2017
| DM Status and Influenza Season | Hospitalization Rate |
ICU Admission Rate |
Pneumonia Rate |
Mechanical Ventilation Rate | In-Hospital Death Rate |
|---|---|---|---|---|---|
| With DM | |||||
| Influenza season | |||||
| All 5 seasons | 276 (230–330) | 42 (35–51) | 64 (53–77) | 17 (14–20) | 11 (9–13) |
| 2012–2013 | 223 (185–267) | 38 (30–47) | 51 (41–62) | 16 (13–21) | 8 (6–11) |
| 2013–2014 | 123 (102–148) | 24 (19–30) | 38 (30–46) | 10 (8–13) | 5 (4–8) |
| 2014–2015 | 395 (329–473) | 58 (47–71) | 87 (72–106) | 24 (20–29) | 15 (12–19) |
| 2015–2016 | 121 (100–145) | 23 (18–28) | 33 (27–41) | 9 (7–12) | 5 (4–7) |
| 2016–2017 | 366 (306–439) | 56 (46–68) | 87 (72–106) | 21 (17–25) | 15 (12–19) |
| Without DM | |||||
| Influenza season | |||||
| All 5 seasons | 181 (150–217) | 23 (19–28) | 42 (34–51) | 9 (8–10) | 7 (6–9) |
| 2012–2013 | 150 (124–181) | 21 (17–25) | 37 (30–45) | 8 (6–9) | 7 (4–9) |
| 2013–2014 | 72 (59–87) | 13 (10–16) | 20 (16–25) | 6 (5–7) | 4 (3–5) |
| 2014–2015 | 262 (217–316) | 32 (26–39) | 61 (50–74) | 13 (11–16) | 10 (8–13) |
| 2015–2016 | 69 (57–83) | 11 (9–13) | 18 (15–22) | 5 (4–6) | 3 (2–4) |
| 2016–2017 | 233 (193–281) | 30 (24–36) | 52 (43–64) | 10 (8–12) | 9 (7–12) |
Data are presented as rates per 100 000 (95% confidence interval). Data source: Influenza Hospitalization Surveillance Network (FluSurv-NET), 2012–2013 through 2016–2017.
Abbreviations: DM, diabetes mellitus; ICU, intensive care unit.
The pooled rate ratio of each influenza-associated outcome among people with DM vs those without DM were as follows: influenza-associated hospitalization, 1.57 (95% CI, 1.43–1.72); ICU admission, 1.84 (95% CI, 1.67–2.04); pneumonia, 1.57 (95% CI, 1.42–1.73); mechanical ventilation, 1.95 (95% CI, 1.74–2.20); and in-hospital death, 1.48 (95% CI, 1.23–1.80). In each of the 2012–2013 through 2016–2017 influenza seasons, the rates of influenza-associated hospitalization, ICU admission, pneumonia, and mechanical ventilation were significantly higher among those with DM than among those without DM (Table 3).
Table 3.
Rate Ratios of Hospitalization, Intensive Care Unit Admission, Pneumonia, Mechanical Ventilation, and In-Hospital Death Among Adults With and Without Diabetes Mellitus—Influenza Hospitalization Surveillance Network (FluSurv-NET) and Centers for Medicare and Medicaid Services, 2012–2017
| Influenza Season | Hospitalization |
ICU Admission | Pneumonia | Mechanical Ventilation | In-Hospital Death |
|---|---|---|---|---|---|
| All 5 seasons | 1.57 (1.43–1.72) | 1.84 (1.67–2.04) | 1.57 (1.42–1.73) | 1.95 (1.74–2.20) | 1.48 (1.23–1.80) |
| 2012–2013 | 1.49 (1.34–1.66) | 1.78 (1.51–2.10) | 1.40 (1.21–1.62) | 2.13 (1.66–2.72) | 1.37 (.97–1.94) |
| 2013–2014 | 1.74 (1.54–1.96) | 1.84 (1.51–2.23) | 1.79 (1.51–2.12) | 1.78 (1.34–2.37) | 1.45 (.94–2.21) |
| 2014–2015 | 1.51 (1.36–1.66) | 1.78 (1.55–2.04) | 1.44 (1.28–1.62) | 1.80 (1.49–2.17) | 1.44 (1.10–1.87) |
| 2015–2016 | 1.75 (1.56–1.97) | 2.06 (1.69–2.51) | 1.80 (1.52–2.13) | 2.04 (1.51–2.75) | 1.68 (1.11–2.57) |
| 2016–2017 | 1.56 (1.41–1.72) | 1.87 (1.63–2.15) | 1.63 (1.45–1.84) | 2.09 (1.71–2.55) | 1.54 (1.19–2.00) |
Data are presented as rate ratios (95% confidence intervals), which were obtained from random-effects meta-analysis models. Data source: Influenza Hospitalization Surveillance Network (FluSurv-NET), 2012–2013 through 2016–2017.
Abbreviation: ICU, intensive care unit.
DISCUSSION
This analysis was conducted to estimate rates of severe influenza-associated outcomes among adults aged ≥65 years with and without DM in the US. We found that among adults aged ≥65 years hospitalized with influenza from 2012–2013 through 2016–2017 and reported to FluSurv-NET, more than one-third had DM. On average, there were 276 influenza-associated hospitalizations per 100 000 person-years in adults aged ≥65 years with DM within the FluSurv-NET catchment areas. Across all seasons, the rate of influenza-associated hospitalizations in people with DM was almost 60% greater than in those without DM. Furthermore, the rates of ICU admission, pneumonia, mechanical ventilation, and in-hospital death in those with DM were higher than the rates in those without DM. Variability in rates of severe outcomes across the 5 influenza seasons may have been due in part to differences in circulating influenza virus types and subtypes [23], severity of the influenza season [24], and vaccine effectiveness [25].
Previous studies have shown that DM may increase the risk of severe outcomes of influenza [12, 26]. One study conducted during the 2009 influenza A(H1N1) pandemic demonstrated that DM may double the risk of influenza-associated death and increase the odds of influenza-associated ICU admission by 4.29 times compared with those without DM [15]. From a pathophysiologic standpoint, animal models have demonstrated that glycemic variability, which is associated with markers of oxidative stress and hyperinflammation, may increase severity of influenza infection [27]. Our findings support the current evidence that DM increases the risk of severe influenza-associated outcomes in adults aged ≥65 years in the US.
The majority of people with DM have at least 1 additional chronic comorbidity [28–30]. Commonly reported comorbidities among persons with DM include hypertension, chronic kidney disease, cardiovascular disease, and obesity [28–30]. FluSurv-NET data previously demonstrated that during the 2010–2011 through 2017–2018 influenza seasons, almost 12% of adults hospitalized with influenza experienced an acute cardiovascular event, with acute heart failure and acute ischemic heart disease being the most commonly reported [31]. DM, cardiovascular diseases, chronic kidney disease, and obesity, among other factors, were shown to independently increase the risk of acute heart failure and acute ischemic heart disease [31]. In the present analysis, we were unable to determine the prevalence of comorbidities among people with and without DM residing in the FluSurv-NET catchment area (source population); however, among the hospitalized FluSurv-NET patients, we found that the prevalence of cardiovascular disease, obesity, and chronic renal disease was higher among those with DM compared with those without DM. Future studies should assess whether accompanying comorbidities further increase the risk of severe influenza-associated outcomes in people with DM.
The results of the present analysis have implications for influenza prevention and control strategies. As the prevalence of DM and obesity in the US continues to increase [32, 33], rates of severe influenza-associated outcomes among older adults may also increase. Persons with DM should receive annual influenza vaccination [34]; prior FluSurv-NET analyses have demonstrated that influenza vaccination can attenuate disease severity among people hospitalized with influenza [6]. Data from the National Health Interview Survey showed that influenza vaccination coverage during the 2017–2018 season was 75% and 71% among adults aged ≥65 years with and without DM, respectively [35], suggesting room for improved vaccine uptake in this population. Annual influenza vaccination should be part of the routine preventive health services offered to every adult with DM. Early antiviral treatment is also recommended for confirmed or suspected influenza among persons ≥65 years as well as persons with DM or other chronic underlying conditions, regardless of hospitalization status [34]. While we were not able to specifically assess these factors, optimizing glycemic control [36, 37] among persons with DM may help reduce the risk of severe influenza-associated outcomes.
The results of the present analysis should be interpreted with the following limitations in mind. All rates and rate ratios reported in this analysis were unadjusted, so they are subject to confounding effects of other important variables, including age, race/ethnicity, sex, chronic comorbidities, and vaccination status. The FluSurv-NET catchment area covers 9% of the US population and findings may not be nationally generalizable. Methods for defining DM varied between CMS and FluSurv-NET; while CMS used ICD codes from insurance claims to identify DM, FluSurv-NET obtained data on DM through medical chart abstractions. The ICD codes that were used by CMS to define DM included conditions that may be temporary, including drug-induced or chemically induced DM; thus, CMS claims data may have overestimated the true population prevalence of DM. For instance, DM prevalence among US adults aged ≥65 years in 2016 was about 21% based on data from the National Health Interview Survey [11], compared with 27% based on CMS data. Overestimation of DM prevalence in the underlying population would have led to underestimation of rates and relative risks for the selected outcomes among adults with DM in our analysis. If this overestimation were to be corrected, the rate ratios reported in our analysis would be expected to increase, further strengthening our conclusions. Because FluSurv-NET does not collect information on type 1 vs type 2 DM, diabetic treatment, or glycemic control among those with DM, we were unable to account for these factors in our analysis. Finally, providers may have been more likely to hospitalize people with DM, even with less severe influenza, than those without DM. This potential admission bias, which we were unable to account for, might have impacted rate ratios for influenza-associated hospitalizations among persons with and without DM.
This analysis, conducted over multiple seasons using a population-based and geographically diverse surveillance network, provides robust data to add to the evidence of the impact of DM on severe influenza-associated outcomes among adults aged ≥65 years in the US. The results could help guide public health and clinical practice in the care of diabetic patients including promoting annual influenza vaccination, advocating for patients to seek healthcare early, and encouraging healthcare providers to have a low threshold for early diagnosis and treatment of influenza.
Supplementary Data
Supplementary materials are available at Open Forum Infectious Diseases online. Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.
Notes
Acknowledgments. The authors thank the following additional persons for their contributions at the Centers for Disease Control and Prevention (CDC) and the participating FluSurv-NET sites: Susan Fuller, MBS, Rainy Henry, Sonja Nti-Berko, MPH, Robert Pinner, Alissa O’Halloran, MSPH, Charisse Cummings, MPH (CDC); Mimi Huynh, MPH (Council of State and Territorial Epidemiologists [CTSE]); Susan Brooks, MPH, Erin Parker, MPH, Mirasol Apostol, MPH, Maria Rosales, MPH (California); Matthew Cartter, MD, MPH, Amber Maslar, MPA, Tamara Rissman, MPH, Kimberly Yousey-Hindes, MPH (Connecticut); Emily Fawcett, MPH, Suzanne Segler, MPH, Stepy Thomas, MSPH, Kyle Openo, DrPH, Monica Farley, MD (Georgia); Alicia Brooks, MPH, Patricia Ryan, MSc, David Blythe, MD, MPH (Maryland); Jim Collins, MPH, RS, Shannon Johnson, MPH, Justin Henderson, MPH (Michigan); Melissa McMahon, MPH, Craig Morin, MPH, Erica Bye, MPH, Team Flu (Minnesota); Sarah A. Khanlian, MPH, Katarina Manzi, BS, Elizabeth Dufort, MD (New York); Krista Lung, MPH, Nicholas Fisher, BS (Ohio); Magdalena Scott, MPH, Courtney Crawford, MPH (Oregon); Amanda Carter, BS, Andrea George, MPH, Andrea Price, LPN, Andrew Haraghey, BS, Ashley Swain, CHES, CaitlinShaw, BS, Ian Buchta, MPH, Jake Ortega, MPH, Keegan McCaffrey, BS, Laine McCullough, MPH, Mary Hill, MPH, Melanie Crossland, MPH, Tyler Riedesel, MPH (Utah).
Disclaimer. The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the CDC.
Financial support. This work was supported by the CDC through an Emerging Infections Program cooperative agreement (grant number CK17-1701) and through a CSTE cooperative agreement (grant number NU38OT000297-02-00).
Potential conflicts of interest. E. J. A. reports grants for clinical trials from Pfizer, Merck, PaxVax, Micron, Sanofi-Pasteur, Janssen, MedImmune, and GSK; consulting fees from Sanofi-Pasteur, Pfizer, Janssen, and Medscape; personal fees for data and safety monitoring board participation from Kentucky Bioprocessing, Inc and Sanofi Pasteur; and institutional funding from the National Institutes of Health to conduct clinical trials of the Moderna and Janssen COVID-19 vaccines. L. B. reports grants from CSTE. J. M. and M. M. report grants from CDC’s Emerging Infections Program. S. K. reports grants from the Michigan Department of Health and Human Services (CSTE Federal Grant). R. L. reports grants from CDC and is a co-editor of the American Academy of Pediatrics Report of the Committee of Infectious Diseases (Red Book; with fee given to the Minnesota Department of Health). W. S. reports grants from CDC and personal fees from VBI Vaccines. All other authors report no potential conflicts of interest.
All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
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