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TABLE III. Deaths in 122 U.S. cities,' week ending March 29, 2008 (13th Week)
All causes, by age (years)

All causes, by age (years)
All
P&It

PH Reporting Area Ages >65 45-64 25-44 1-24 <1 Total Reporting Area Ages >65 45-64 25-44 1-24

Total New England 635 464 122 27 7 14 79

S. Atlantic

1,086 708 259 68 35 15 Boston, MA 129 81 30 9 2 6 18

Atlanta, GA
103 61 28 10 3

1 Bridgeport, CT

35 22

12
1

4
Baltimore, MD
133 78 39

8 5 2 Cambridge, MA 12 10 2

2. Charlotte, NC

102 64 28

5 3 2 Fall River, MA 31 27 3

1
3 Jacksonville, FL
166 105 41 13 6

1 Hartford, CT 63 37 19

1
4 6
Miami, FL
82 62 14 3 2

1 Lowell, MA

33 24

5
4

5
Norfolk, VA
57 33 19

3 2 Lynn, MA

12
8
2
2.

1
Richmond, VA
61 44 13

2. 1

1 New Bedford, MA

35 27

7
1

1
Savannah, GA
65 42 16

5 2 New Haven, CT

43 37

3
3

12
St. Petersburg, FL

66 47

7
5 4

3 Providence, RI

80 67

8
3

7
Tampa, FL
236 163 49 16 6

2. Somerville, MA

2
1
1

1
Washington, D.C.

U U U U
Springfield, MA

49 36

11
1
1 7
Wilmington, DE

15
9
5

1 Waterbury, CT

34 27
5

1 5
Worcester, MA
77 60 15

E.S. Central
1
1 7

1,022 689

222

69 23 18 Birmingham, AL

197 132 45 17 2 1 Mid. Atlantic 2,180 1,554 438 101 46 37 131

Chattanooga, TN
133 104 19

6 3 Albany, NY

54 41

7
3 2 1 4

Knoxville, TN
126 90 21

8 4

3 Allentown, PA

28 24

2

1
1

1
Lexington, KY

79 51

18
7 2

1 Buffalo, NY 74 57 12 3 2

8
Memphis, TN
131 100 20 7 3

1 11 Camden, NJ 32 19 9 2 1

1
Mobile, AL

119 67 39 9 2 2 11 Elizabeth, NJ

25 16

6
2. 1

1
Montgomery, AL

42 19

4

1 2 Erie, PA 52 40 11

1

5
Nashville, TN
169 103 41 11 6

8 Jersey City, NJ 26 13 10

1

2 2 New York City, NY 1,114 801 219

W.S. Central 52 27 12 48

1,676 1,076

118 36 33 Newark, NJ 46 24 13

Austin, TX 4

122 79 1

2
4

28
6

4 Paterson, NJ

27 22
4

Baton Rouge, LA

53
1
3

34
12
3

2 Philadelphia, PA 247 142 66 17

Corpus Christi, TX 13

62 8

48 12 11

2
Pittsburgh, PAS
50 39

Dallas, TX
9
1

218
5
1

120 61 25 10

2 Reading, PA 34 28

El Paso, TX

141 104 1

3 1

21 10

4 Rochester, NY 139 112 21

Fort Worth, TX

147 103 17

36 3

3 Schenectady, NY 26 22

Houston, TX 4

285 158 81 34 Scranton, PA 33 30

Little Rock, AR 3

85 4

53 19

9 Syracuse, NY 115 83 26

New Orleans, LAI

U
3
10

U U

U Trenton, NJ 23 15

San Antonio, TX 5

295 2

202 77 10

4 Utica, NY

14
12
2.

Shreveport, LA
3

108 73 18

9 2 6 Yonkers, NY

21 14

5
2

Tulsa, OK

160

47

7 2 2 16 E.N. Central 2,456

Mountain 1,605 591 142 44 74 204

1,316 891 276 83 32 30 Akron, OH 64 39 16

4
4
Albuquerque, NM

144 107 25
1 1

9
1

2 15 Canton, OH 61 40 17 1

Boise, ID 3 7

68 15 6

5 11 Chicago, IL 390 251

Colorado Springs, CO 95 28 6 10

45 43

16

1 10

2 Cincinnati, OH 122 74 25

Denver, CO

114 8

30 2 13

68 18

10

4 Cleveland, OH

316
222 79

Las Vegas, NV

291
4
3 8 17

195 69 19

3 23 Columbus, OH 214 131 59 14 3 7

4 Ogden, UT

30 22

22

1 Dayton, OH

148
105 29
6 3 5

Phoenix, AZ

203 14

132 43 10 6 9 Detroit, MI 216 99 67 38

Pueblo, CO
4
8

25
15

3
2.

3

1 Evansville, IN 59 46 11

Salt Lake City, UT 138 1

2 1

86 33 8 7 4 14 Fort Wayne, IN 89 57 26

Tucson, AZ
4
2

192
8

143 38

8 2 1 15 Gary, IN

15
7
4
2 2

1
Pacific

1,799 1,278 354 99 43 24 16 Grand Rapids, MI

34 24

7

1
2

1
Berkeley, CA

19 10

8

1
Indianapolis, IN
214 143 50

8
6
7 18
Fresno, CA
143 99 29 10

1 Lansing, MI 55 36 15

4

2
Glendale, CA

20 17

3
Milwaukee, WI
116 75 33

4 1
3 6
Honolulu, HI
86 64 15

5
Peoria, IL
66 40 16
3 2 5 7 Long Beach, CA

87 55 16 11

2 9 Rockford, IL

62 53

3
3
3
8 Los Angeles, CA

276 193 48 14 17 4 South Bend, IN 59 40 15

3
1 5 Pasadena, CA

15

4
Toledo, OH
101 71 21

6
2 1 4
Portland, OR
113 73 31

9
Youngstown, OH
55 52 3

5
Sacramento, CA
213 163 37

9 2 2 23 W.N. Central 640 451 122 34 16 16

San Diego, CA 70

174 122 37

8

1 Des Moines, IA

76 61
11

San Francisco, CA
2

126
1
1

81
4

31 11

3 Duluth, MN 48 36 9

San Jose, CA

189 8

144
3

34
5

5 Kansas City, KS 23 18 3

2
Santa Cruz, CA

32 26

4

2 Kansas City, MO 104 71 23

Seattle, WA

122 76 30
1
5

8

4 Lincoln, NE 33 23 10

Spokane, WA

66 53

9
1

1
4

2 Minneapolis, MN 77 46 13 10 5

Tacoma, WA

87 9

18 3

5 3
Omaha, NE
101 70 23

6
1 14
Total

12,810** 8,716 2,796 741 282 261 1.088 St. Louis, MO

34 16

9
5 1

2 3 St. Paul, MN

64 53

7

1

3 12 Wichita, KS 80 57 14

7 1

1 6 U: Unavailable. -:No reported cases. * Mortality data in this table are voluntarily reported from 122 cities in the United States, most of which have populations of 2100,000. A death is reported by the place of its

occurrence and by the week that the death certificate was filed. Fetal deaths are not included. * Pneumonia and influenza. 5 Because of changes in reporting methods in this Pennsylvania city, these numbers are partial counts for the current week. Complete counts will be available in 4 to 6 weeks 1 Because of Hurricane Katrina, weekly reporting of deaths has been temporarily disrupted. ** Total includes unknown ages.

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Prevalence of Self-Reported Postpartum Depressive Symptoms

17 States, 2004-2005 Postpartum depression (PPD) affects 10%-15% of mothers these 17 states included two questions on self-reported PDS ithin the first year after giving birth (1). Younger moth- in their PRAMS surveys: 1) “Since your new baby was born, s and those experiencing partner-related stress or physi- how often have you felt down, depressed, or hopeless?" and I abuse might be more likely to develop PPD (2,3). CDC 2) “Since your new baby was born, how often have you had ialyzed data from the Pregnancy Risk Assessment Moni- little interest or little pleasure in doing things?” The ring System (PRAMS) for 2004–2005 (the most recent response choices were “always,” “often,” “sometimes,” ita available) to 1) assess the prevalence of self-reported “rarely,” and “never”; women who said “often” or “always” pstpartum depressive symptoms (PDS) among mothers to either question were classified as experiencing selfy selected demographic characteristics and other possible reported PDS. Because of their high sensitivity (96%), these sk factors for PDS and 2) determine factors that identify two questions have been recommended as a depression case

others most likely to develop PPD. This report summa- finding instrument by health professionals (5,6). Chi-square zes the results of that analysis, which indicated that, dur- tests were used to test for significant differences (p<0.05) ig 2004–2005, the prevalence of self-reported PDS in 17 in the proportion of women reporting PDS by demographic .S. states* ranged from 11.7% (Maine) to 20.4% (New characteristics and other possible risk factors for PDS within lexico). Younger women, those with lower educational each of the 17 states; approximate 95% confidence interItainment, and women who received Medicaid benefits vals for these proportions were calculated. To measure the br their delivery were more likely to report PDS. State and strength of the association overall, the median difference pcal health departments should evaluate the effectiveness across all states in the proportion of women reporting PDS f targeting mental health services to these mothers and between two levels of each covariate was calculated. Sample ncorporating messages about PPD into existing programs -G., domestic violence services) for women at higher risk.

* Confidence intervals are approximate because, when adjusting for the clustered PRAMS is an ongoing, state-specific, population-based survey design, the confidence intervals computed were close to but not equal to

+1.96 x standard error. prveillance project that collects self-reported information n maternal attitudes and experiences before, during, and

INSIDE fter delivery of a live infant. PRAMS is administered by !DC in collaboration with participating states and cities

366 Preliminary FoodNet Data on the Incidence of Infection

with Pathogens Transmitted Commonly Through Food ad is designed to be representative of women in partici

10 States, 2007 ating states who have delivered during the preceding 2–6 370 Malnutrition and Micronutrient Deficiencies Among tonths (4). Response rates were 270% for 2004 and 2005

Bhutanese Refugee Children — Nepal, 2007 I each of the 17 participating states. During 2004–2005, 373 Automated Detection and Reporting of Notifiable

Diseases Using Electronic Medical Records Versus

Passive Surveillance -- Massachusetts, June 2006-July 2007 Maska, Colorado, Georgia, Hawaii, Maryland, Maine, Minnesota, North Carolina, 376 Notice to Readers Nebraska, New Mexico, New York (excluding New York City), Oregon, Rhode 377 QuickStats sland, South Carolina, Utah, Vermont, and Washington.

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DEPARTMENT OF HEALTH AND HUMAN SERVICES

CENTERS FOR DISEASE CONTROL AND PREVENTION

The MMWR series of publications is published by the Coordinating
Center for Health Information and Service, Centers for Disease
Control and Prevention (CDC), U.S. Department of Health and
Human Services, Atlanta, GA 30333.
Suggested Citation: Centers for Disease Control and Prevention.
[Article title]. MMWR 2008;57:[inclusive page numbers).
Centers for Disease Control and Prevention
Julie L. Gerberding, MD, MPH

Director
Tanja Popovic, MD, PhD

Chief Science Officer
James W. Stephens, PhD
Associate Director for Science

Steven L. Solomon, MD
Director, Coordinating Center for Health Information and Service

Jay M. Bernhardt, PhD, MPH
Director, National Center for Health Marketing

Katherine L. Daniel, PhD
Deputy Director, National Center for Health Marketing
Editorial and Production Staff

Frederic E. Shaw, MD, JD
Editor, MMWR Series

Teresa F. Rutledge
(Acting) Managing Editor, MMWR Series

Douglas W. Weatherwax
Lead Technical Writer-Editor
Donald G. Meadows, MA

Jude C. Rutledge

Writers-Editors

Peter M. Jenkins
(Acting) Lead Visual Information Specialist

Lynda G. Cupell

Malbea A. LaPete
Visual Information Specialists
Quang M. Doan, MBA

Erica R. Shaver
Information Technology Specialists

sizes varied for each estimate because women who wa. missing data on any variable (<5% of all women) e excluded from analysis of that variable. The analysis a conducted using statistical software to adjust for the cos plex survey design and produce statewide estimates. Esri mates based on small sample sizes (fewer than : respondents) were considered to be unreliable.

The maternal characteristics analyzed included age a delivery, race/ethnicity, education, marital status, a. receipt of Medicaid for delivery. Possible risk factors for PL included in the analysis were low infant birth weig (<2,500 g), admission to a neonatal intensive-care un (NICU), number of previous live births, tobacco use du ing the last 3 months of pregnancy, physical abuse befo or during pregnancy, and experiencing emotional, fina cial, partner-related, or traumatic stress during the months before delivery. Women were considered physical abused if they said that a current or former husbaru partner had pushed, hit, slapped, kicked, choked, or phu cally hurt them in any way during the 12 months before or during the most recent pregnancy. Women who reporte smoking one or more cigarettes on an average day were classified as using tobacco during the last 3 months pregnancy.

During 2004–2005, overall prevalence of self-reporici PDS ranged from 11.7% (Maine) to 20.4% (New Mexico (Table 1). Demographic characteristics significantly assciated with PDS in all of the 17 states were maternal ag: marital status, maternal education, and Medicaid covera: for delivery. Among the 17 states, the median percentag point difference in PDS prevalence was 13.4 percentan points between the youngest and oldest mothers, 134 between the lowest and highest education groups, 9.7 b marital status, and 11.0 by Medicaid receipt. In 13 of the 16 states for which data were available, a significant asse ciation was observed between race/ethnicity and PDS, with non-Hispanic white women having a lower prevalence PDS compared with women of other racial/ethnic group

PDS was significantly associated with five possible risk factors in all or nearly all of the 17 states (Table 2). Thi number of states with significant associations and state

Editorial Board William L. Roper, MD, MPH, Chapel Hill, NC, Chairman

Virginia A. Caine, MD, Indianapolis, IN

David W. Fleming, MD, Seattle, WA
William E. Halperin, MD, DrPH, MPH, Newark, NJ
Margaret A. Hamburg, MD, Washington, DC
King K. Holmes, MD, PhD, Seattle, WA
Deborah Holtzman, PhD, Atlanta, GA

John K. Iglehart, Bethesda, MD
Dennis G. Maki, MD, Madison, WI
Sue Mallonee, MPH, Oklahoma City, OK

Stanley A. Plotkin, MD, Doylestown, PA
Patricia Quinlisk, MD, MPH, Des Moines, IA
Patrick L. Remington, MD, MPH, Madison, WI

Barbara K. Rimer, DrPH, Chapel Hill, NC
John V. Rullan, MD, MPH, San Juan, PR

Anne Schuchat, MD, Atlanta, GA
Dixie E. Snider, MD, MPH, Atlanta, GA

John W. Ward, MD, Atlanta, GA

$ Stressors during pregnancy were categorized as 1) emotional (a very sick for? member had to go into the hospital or someone close to the respondent died financial (the respondent moved to a new address, her husband/partner lose in job, she lost her job, or she had a lot of bills she could not pay; 3) partner-relea (the respondent separated or divorced from her husband/partner, she argumore than usual with her husband/partner, or her husband/partner said he was not want her to be pregnant); and 4) traumatic (the respondent was homes she was involved in a physical fight, she or her husband/partner went to jail. someone close to her had a problem with drinking/drugs).

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