# Presentation: 614325

## INCREASING INFANT MORTALITY RATES (IMR) IN LOUISIANA: Public Health Emergency Or Reporting Artifact?

- Juan M. Acuña M.D.
- CDC Maternal and Child Health Epidemiologist
- Louisiana Office of Public Health

## Background

- Louisiana ranks consistently among the 5 states with the highest IMR
- The IMR decline had followed the US
- The IMR hit a record low in 2000 (8.9. All IMR in deaths per 1000 live births).
- The IMR increased to 9.8 in 2001 and (in recently released data) to 10.2 in 2002.
- Strong political and media attention.
- Data from years 1997 to 2002 was analyzed to explain this increase.

## Methods

**A**nalysis of  Louisiana’s birth file and linked birth-infant/fetal death file
- Data from 1997-2002.
- One-sided Kendall’s Tau-b correlation was used to evaluate statistical significance of trends
- Indirect adjustment of rates and Z scores
- Multivariate analysis models
- GENMODE / GLIMMIX models

## Louisiana’s 64 Parishes and 9 Administrative Regions

- Louisiana’s 64 Parishes and 9 Administrative Regions

## Results – Step I

- Analysis of crude rates:
- Overall crude rates by state and region
- Overall rates by race, birth weight strata including:
- PPOR methodology
- Finer stratification by birth weight categories
- Analysis of reporting of deaths

## Infant mortality rates, all races,, LA 1999-2001

- * p<o.o5

## Feto-Infant Mortality, Louisiana, 1997-2002

**Notes:**
So how are excess mortality rates and numbers calculated?  Let’s take an example.  The excess mortality rates for Phoenix, Arizona for 1995-97 would be calculated as follows:  the Maternal Health/Prematurity rate for all races, 3.7, minus the Maternal Health/Prematurity rate for the previously recommended reference group, 1.6, gives the excess mortality rate, 2.1.  The overall excess feto-infant mortality rate is 10.4 – 6.0 = 4.4. The numbers may not add up exactly because of rounding.  The actual number of excess deaths can be calculated by multiplying the excess mortality rate by the total number of fetal deaths and live births.  Excess mortality rates are calculated and shown for the remaining 3 groups.  

## Slide 8

## Results – Step II

- Adjustment of rates
- Indirect adjustment of overall crude rates
- Stratified adjustment
- By birth weight
- Birth weight specific mortality
- Birth weight distribution

## Slide 10

## Louisiana’s 9 administrative Regions’ births by race

- Black: 48%
- White: 51%

- Black: 35%
- White: 65%

- Black: 30%
- White: 70%

- Black: 55%
- White: 45%

## Adjusted risk for IM, Louisiana  1996-2002

- Adjusted risk for IM, Louisiana  1996-2002

## partial rate

## Mortality

**Birthweight Distribution**

**Birth weight- Specific Mortality**

- Higher rate because there are more small babies

- Higher rate because the babies die more

- Where are we?

- %

- has two components: BWD and BWSM

## Perinatal mortality Hospital X

**Birth Weight    ****BWSM****  ****BWD**

- PMR: **22.6** per 1000 LB+ FD

## Results - Step III

- Multivariate analysis
- Adjusted regression models including confounders and interaction models (assuming independence of variables)
- GENMODE / GLIMMIX models
- Analysis of correlated data (non-independence for variables such as level of attention, access to services, prenatal care, etc)

## Multivariable Analysis

| Risk factors |  |  | OR (95% CI) | P value | Reference |
| --- | --- | --- | --- | --- | --- |
| Education  | <10 grade |  | 2.1 (1.6, 2.7) | 0.000 | > 12 grade |
|  | 10-12 grade |  | 1.6 (1.3, 1.9) | 0.000 |  |
| Marital | Not married |  | 1.2 (1.0, 1.4) | 0.046 | Married |
| Gender | Male |  | 1.3 (1.1, 1.4) | 0.001 | Female |
| Prenatal care | Intermediate |  | 1.2 (0.9, 1.5) | 0.125 | Adequate |
|  | Inadequate |  | 1.2 (1.0, 1.5) | 0.048 |  |
| Gestation | 24-36 weeks |  | 2.3 (1.8, 2.8) | 0.000 | > 36 weeks |
| Race | White | 500-1499 | 30.1(22.3,43.1) | 0.000 | >= 2500 grams |
|  |  | 1500-2499 | 4.43.35.9 | 0.000 |  |
|  | Black | 500-1499 | 11.1 (8.2, 15.0) | 0.000 | >= 2500 grams |
|  |  | 1500-2499 | 2.0 (1.5, 2.6) | 0.000 |  |
| Birth weight
(grams) | 500-1499 | White | 1.9 (1.6, 2.2) | 0.000 | Black |
|  | 1500-2499 | White | 1.5 (1.1, 1.9) | 0.000 | Black |
|  | >=2500 | Black | 1.5 (1.2, 1.8) | 0.000 | White |

## Conclusions

- One size does not fit all
- Neither crude nor adjusted rates are the only analytical tools for the analysis of risk [for death] in a complex [state] population
- Analysis of reporting is mandatory
- Be creative, be careful (program and policy people rely on your skills)

## Crude Rates

- Crude rate errors

- Adjusted rates

- Multivariate analysis

- Correlation analysis

- GIS

- Trend analysis

- Survival analysis

- At least do:

- Analytical Model