A Multiple Cause Analysis of Infectious Disease Mortality in Massachusetts,2002-2011DAVID MEYERS

Background Infectious disease mortality accounts totally for 3% of all deaths in the state looking at underlying cause

There may be a recent resurgence of conditions such as sepsis, HIV and Hepatitis C

Long term trends in deaths data are not commonly examined in Massachusetts

Underlying Cause of Death alone may not account for the full extent of infectious disease related mortality

Driving Questions What is the extent of mortality related to infectious disease in Massachusetts over the past decade?

How is infectious disease related mortality in Massachusetts distributed across age, gender, and race?

How is infectious disease related mortality in Massachusetts distributed in space and time?

Methods 4 Infectious Diseases were identified based on prevalence and public health importance to be the focus of analysis

◦ Sepsis, Influenza/Pneumonia, Hepatitis C (HCV), HIV/AIDS

All deaths with any Infectious disease ICD code were pulled from the Massachusetts Death Certificate Database from 2002-2011

Shapefiles for Massachusetts Census Tracts were taken from MassGIS

Analysis and data management took place in SAS, ArcGIS, Joinpoint, and SatScan

Methods (continued) Age-Adjusted Standardized Mortality Rates were calculated by race, age, and gender for each ID of interest

Trends in mortality over time were calculated in the Joinpoint Regression Program

Spatial clusters of mortality were examined using a 5-step geo-processing approach

Spatial-Temporal Clusters were examined using a Discrete Poisson space-time model in SatScan

Results

Results 91,208 deaths were associated with infectious disease causes over the ten-year period

2,913 deaths were associated with Hepatitis C

1,905 deaths were associated with HIV

33,858 deaths were associated with Sepsis

55,718 deaths were associated with Influenza/Pneumonia

ICD total Code Category

A04 2428 Other bacterial intestinal infections (E.Coli, campylobacter enteritis, Yersinia enterocolitica, clostridium difficile, etc…)

A49 1587 Bacterial infection of unspecified site (Staph, Strep, Haemophilus influenza, mycoplasma, other)

B94 650 Sequelae of other and unspecified infectious and parasitic diseases (trachoma, viral encephalitis, viral hepatitis, other)

A09 437 Infectious gastroenteritis and colitis

B99 377 Other and unspecified infectious diseases

B49 225 Unspecified mycosis

A81 189 Atypical virus infections of central nervous system

B91 189 Sequelae of poliomyelitis

B34 175 Viral infection of unspecified site

A16 160 Respiratory Tuberculosis

B02 146 Zoster [herpes zoster]

B37 128 Candidiasis

B44 124 Aspergillosis

What is the extent of mortality related to HCV over a ten year period?

2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

50100150200250300350400450500

89 63 72 59 67 88 98 110 121 110

271236 250

196 220267 290 295

321 297

Year

HCV

Dea

ths

What is the extent of mortality related to HIV over a ten year period?

2002 2003 2004 2005 2006 2007 2008 2009 2010 20110

50

100

150

200

250

300

229 227 211180 179

143 143 124 11991

32 30 36

26 17

22 19 33 2717

Underlying Cause Contributing Cause Only

Year

HIV

Dea

ths

How is HCV Mortality Distributed across Race?

White non-Hispanic Black non-Hispanic Hispanic Asian non-Hispanic Massachusetts Overall0

20

12.6 3.4

0.9 1.21.9

7.47

1.72.4

2.9

10.0 10.4

2.63.6

Contributing Cause Only

Underlying Cause

Age-

adju

sted

HCV

dea

th ra

tes

per 1

00,0

00

How is HIV Mortality Distributed across Race?

White non-Hispanic Black non-Hispanic Hispanic Asian non-Hispanic Massachusetts Overall0

2

4

6

8

10

12

14

16

1.3

12.8

9.3

0.62.40.3

1.5

1.4

0

0.41.6

14.3

10.7

0.6

2.8

Contributing Cause Only

Underlying Cause

Age-

adju

sted

dea

th ra

tes

per 1

00,0

00

How is HCV Mortality Distributed Across Age?

<15 15-24 25-34 35-44 45- 54 55-64 65- 74 75-84 85+0

200

400

600

800

1,000

1,200

1,400

0 5 8 88377 346

82 70 260 1 35

273

766559

142 9440

Underlying Contributory

Age groups (years)

HCV

Dea

ths

How is HIV Mortality Distributed Across Age?

<15 15-24 25-34 35-44 45- 54 55-64 65- 74 75-84 85+0

50100150200250300350400450500

1 5 888

377 346

82 70261 1 2

64

9972

16 40

ContributoryUnderlying

Age groups (years)

HIV

Dea

ths

Underlying Cause of Death when HCV is Contributing Cause of Death

General Underlying Cause of Death Specific Underlying Cause of Death Count of Deaths

Malignant neoplasms Cancer 608

Infectious Disease HIV/AIDS 369

Digestive System Chronic liver disease 246

Diseases of the circulatory system Heart Disease 158

External Cause Unintentional Injuries 59

Mental or Behavioral Other 46

Genitourinary System Nephritis 45

Infectious Disease Septicemia 43

Digestive System Other 43

Endocrine, Nutritional, and Metabolic

Diabetes 35

Underlying Cause of Death when HIV is Contributing Cause of Death

General Underlying Cause of Death Specific Underlying Cause of Death

Count of Deaths

Malignant neoplasms Cancer 103

Diseases of the circulatory system Heart Disease 38

Digestive System Chronic liver disease 20

Respiratory System Chronic Lower Respiratory Disease

18

Endocrine, Nutritional, and Metabolic Diabetes 12

Mental or Behavioral Other 11

External Cause Unintentional Injuries 9

External Cause Injuries of Undetermined Intent

8

Diseases of the circulatory system hypertension 7

Digestive System Other 6

What trends exist in HCV Mortality?

2002 2003 2004 2005 2006 2007 2008 2009 2010 20110.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

3.2

14.3

12

HCV Ten Year Trend All Races

Adjusted White Adjusted Black Adjusted Hispanic Adjusted Asian

Ag

e-a

dju

ste

d d

ea

th r

ate

s

pe

r 1

00

,00

0 p

op

ula

tio

n

What trends exist in HIV Mortality?

2002 2003 2004 2005 2006 2007 2008 2009 2010 20110.0

5.0

10.0

15.0

20.0

25.0

2.3

22.3

14.7

HIV Ten Year Trend All Races

Adjusted White Adjusted Black Adjusted Hispanic Adjusted Asian

Ag

e-a

dju

ste

d d

ea

th r

ate

s

pe

r 1

00

,00

0 p

op

ula

tio

n

10 Year Average Annual Percent Change in Age Adjusted Mortality by Condition and Race

Race All SepsisFlu/PneumoniaHIV Hepatitis HCV

Total -0.79* -.82* -3.9* -9.79* .99 1.11

White -0.41* -.65* -3.85* -11.13*.93 6.37*^

Black

-2.42*-8.75*^^ -4.65* -5.9* -10.71*-2.18 -2.98

Asian

-7.07* -5.02*^ 5.7* -2.7* n/a 8.77 6.37

Hispanic -5.86* -1.57* -4.18* -10.33*-1.05 -0.65

* denotes statistical significance at the .05 level^ Starting in 2005^^Starting in 2009

Spatial Clusters

Discussion and Conclusions

Discussion Clear disparities exist across race and age groups in each investigated disease

There are clear locations around the state that merit further investigation

◦ South Boston, Worcester, Springfield, New Bedford, Dracut

Significant space-time clustering has occurred

Limitations Death certificates are not always accurate, especially in regards to race and contributing cause of death

Spatial and space-time clusters are difficult to distinguish from noise

It is difficult to select scanning windows in SaTScan

The infectious disease may have been a chronic condition and less of a cause of death

Conclusions Multiple Cause Data is an underutilized resource

There exist clear populations and locations that should be the center of public health focus

Spatial Cluster, and Space-time cluster analyses are valuable resources for mortality data analysis

Acknowledgements Malena Hood

Thomas Stopka

Brandon Olsen

Christine Rioux

Division of Research and Epidemiology, BHIRSE

References Bosetti, C., Bertuccio, P., Levi, F., Lucchini, F., Negri, E., & Vecchia, C. L. (2008). Cancer mortality in the European Union, 1970–2003, with a joinpoint analysis. Annals of Oncology, 19(4), 631–640. doi:10.1093/annonc/mdm597

Brun-Buisson C, Doyon F, Carlet J, & et al. (1995). Incidence, risk factors, and outcome of severe sepsis and septic shock in adults: A multicenter prospective study in intensive care units. JAMA, 274(12), 968–974. doi:10.1001/jama.1995.03530120060042

Burra, T., Jerrett, M., Burnett, R. T., & Anderson, M. (2002). Conceptual and practical issues in the detection of local disease clusters: a study of mortality in Hamilton, Ontario. Canadian Geographer / Le Géographe Canadien, 46(2), 160–171. doi:10.1111/j.1541-0064.2002.tb00737.x

Clegg, L. X., Hankey, B. F., Tiwari, R., Feuer, E. J., & Edwards, B. K. (2009). Estimating average annual per cent change in trend analysis. Statistics in Medicine, 28(29), 3670–3682. doi:10.1002/sim.3733

Feikin, D. R., Schuchat, A., Kolczak, M., Barrett, N. L., Harrison, L. H., Lefkowitz, L., … Jorgensen, J. H. (2000). Mortality from invasive pneumococcal pneumonia in the era of antibiotic resistance, 1995-1997. American Journal of Public Health, 90(2), 223–229.

Getis, A., & Ord, J. K. (1992). The Analysis of Spatial Association by Use of Distance Statistics. Geographical Analysis, 24(3), 189–206. doi:10.1111/j.1538-4632.1992.tb00261.x

Gundogdu, I. B. (2010). Applying linear analysis methods to GIS-supported procedures for preventing traffic accidents: Case study of Konya. Safety Science, 48(6), 763–769. doi:10.1016/j.ssci.2010.02.016

Hsu, C. E., Jacobson, H., & Mas, F. S. (2004). Evaluating the disparity of female breast cancer mortality among racial groups - a spatiotemporal analysis. International Journal of Health Geographics, 3(1), 4. doi:10.1186/1476-072X-3-4

Kanjala, C., Alberts, M., Byass, P., & Burger, S. (2010). Spatial and temporal clustering of mortality in Digkale HDSS in rural northern South Africa. Global Health Action, 3. doi:10.3402/gha.v3i0.5236

Kim, H.-J., Fay, M. P., Feuer, E. J., & Midthune, D. N. (2000). Permutation tests for joinpoint regression with applications to cancer rates. Statistics in Medicine, 19(3), 335–351. doi:10.1002/(SICI)1097-0258(20000215)19:3<335::AID-SIM336>3.0.CO;2-Z

Kulldorff, M., Heffernan, R., Hartman, J., Assunção, R., & Mostashari, F. (2005). A Space–Time Permutation Scan Statistic for Disease Outbreak Detection. PLoS Medicine, 2(3), e59. doi:10.1371/journal.pmed.0020059

Lever, A., & Mackenzie, I. (2007). Sepsis: definition, epidemiology, and diagnosis. BMJ : British Medical Journal, 335(7625), 879–883. doi:10.1136/bmj.39346.495880.AE

Ly, K. N., Xing, J., Klevens, R. M., Jiles, R. B., Ward, J. W., & Holmberg, S. D. (2012). The Increasing Burden of Mortality From Viral Hepatitis in the United States Between 1999 and 2007. Annals of Internal Medicine, 156(4), 271–278. doi:10.7326/0003-4819-156-4-201202210-00004

Mackenbach, J. P., Kunst, A. E., Lautenbach, H., Bijlsma, F., & Oei, Y. B. (1995). Competing Causes of Death: An Analysis using Multiple-Cause-of-Death Data from The Netherlands. American Journal of Epidemiology, 141(5), 466–475.

Manton, K. G. (1980). Sex and Race Specific Mortality Differentials in Multiple Cause of Death Data. The Gerontologist, 20(4), 480–493. doi:10.1093/geront/20.4.480

Martin, G. S., Mannino, D. M., Eaton, S., & Moss, M. (2003). The Epidemiology of Sepsis in the United States from 1979 through 2000. New England Journal of Medicine, 348(16), 1546–1554. doi:10.1056/NEJMoa022139

Melamed, A., & Sorvillo, F. J. (2009). The burden of sepsis-associated mortality in the United States from 1999 to 2005: an analysis of multiple-cause-of-death data. Critical Care, 13(1), R28. doi:10.1186/cc7733

Mj, A., & Ee, M. (1994). The epidemiology of viral hepatitis in the United States. Gastroenterology Clinics of North America, 23(3), 437–455.

Nkhoma, E. T., Hsu, C. E., Hunt, V. I., & Harris, A. M. (2004). Detecting spatiotemporal clusters of accidental poisoning mortality among Texas counties, U.S., 1980 – 2001. International Journal of Health Geographics, 3(1), 25. doi:10.1186/1476-072X-3-25

Qiu, D., Katanoda, K., Marugame, T., & Sobue, T. (2009). A Joinpoint regression analysis of long-term trends in cancer mortality in Japan (1958–2004). International Journal of Cancer, 124(2), 443–448. doi:10.1002/ijc.23911

Redelings, M. D., Sorvillo, F., & Simon, P. (2006). A Comparison of Underlying Cause and Multiple Causes of Death: US Vital Statistics, 2000???2001. Epidemiology, 17(1), 100–103. doi:10.1097/01.ede.0000187177.96138.c6

Rosenberg PS, & Biggar RJ. (1998). Trends in hiv incidence among young adults in the united states. JAMA, 279(23), 1894–1899. doi:10.1001/jama.279.23.1894

Sabel, C. E., Wilson, J. G., Kingham, S., Tisch, C., & Epton, M. (2007). Spatial implications of covariate adjustment on patterns of risk: Respiratory hospital admissions in Christchurch, New Zealand. Social Science & Medicine, 65(1), 43–59. doi:10.1016/j.socscimed.2007.02.040

Soufir, L., MD, Timsit, J., MD, Mahe, C., MD, Carlet, J., MD, Regnier, B., MD, & Chevret, S., MD, PhD. (1999). Attributable Morbidity and Mortality of Catheter Related Septicemia in Critically Ill Patients: A Matched, Risk Adjusted, Cohort Study •. ‐ ‐Infection Control and Hospital Epidemiology, 20(6), 396–401. doi:10.1086/iche.1999.20.issue-6

Stopka, T. J., Krawczyk, C., Gradziel, P., & Geraghty, E. M. (2014). Use of Spatial Epidemiology and Hot Spot Analysis to Target Women Eligible for Prenatal Women, Infants, and Children Services. American Journal of Public Health, 104(S1), S183–S189. doi:10.2105/AJPH.2013.301769

Thompson WW, Shay DK, Weintraub E, & et al. (2003). Mortality associated with influenza and respiratory syncytial virus in the united states. JAMA, 289(2), 179–186. doi:10.1001/jama.289.2.179

Woodhead, M. ., Macfarlane, J. ., Mccracken, J. ., Rose, D. ., & Finch, R. . (1987). PROSPECTIVE STUDY OF THE AETIOLOGY AND OUTCOME OF PNEUMONIA IN THE COMMUNITY. The Lancet, 329(8534), 671–674. doi:10.1016/S0140-6736(87)90430-2