	Zip Code	Births / 1,000 Women	vs State	vs National
1.	19061	1.0	31.0(-30.0)#1	32.0(-31.0)#10
2.	19081	1.0	31.0(-30.0)#2	32.0(-31.0)#25
3.	18929	1.0	31.0(-30.0)#3	32.0(-31.0)#28
4.	15071	2.0	31.0(-29.0)#4	32.0(-30.0)#77
5.	15906	2.0	31.0(-29.0)#5	32.0(-30.0)#85
6.	19333	2.0	31.0(-29.0)#6	32.0(-30.0)#88
7.	17322	2.0	31.0(-29.0)#7	32.0(-30.0)#90
8.	15431	2.0	31.0(-29.0)#8	32.0(-30.0)#106
9.	19140	3.0	31.0(-28.0)#9	32.0(-29.0)#110
10.	17046	3.0	31.0(-28.0)#10	32.0(-29.0)#121
11.	18964	3.0	31.0(-28.0)#11	32.0(-29.0)#155
12.	15037	3.0	31.0(-28.0)#12	32.0(-29.0)#170
13.	18801	3.0	31.0(-28.0)#13	32.0(-29.0)#185
14.	16033	3.0	31.0(-28.0)#14	32.0(-29.0)#189
15.	17066	3.0	31.0(-28.0)#15	32.0(-29.0)#200
16.	15834	3.0	31.0(-28.0)#16	32.0(-29.0)#207
17.	18822	3.0	31.0(-28.0)#17	32.0(-29.0)#212
18.	19151	4.0	31.0(-27.0)#18	32.0(-28.0)#232
19.	19138	4.0	31.0(-27.0)#19	32.0(-28.0)#235
20.	15025	4.0	31.0(-27.0)#20	32.0(-28.0)#285
21.	15234	4.0	31.0(-27.0)#21	32.0(-28.0)#301
22.	17003	4.0	31.0(-27.0)#22	32.0(-28.0)#312
23.	17038	4.0	31.0(-27.0)#23	32.0(-28.0)#331
24.	17745	5.0	31.0(-26.0)#24	32.0(-27.0)#463
25.	19390	5.0	31.0(-26.0)#25	32.0(-27.0)#482
26.	15061	5.0	31.0(-26.0)#26	32.0(-27.0)#483
27.	17740	5.0	31.0(-26.0)#27	32.0(-27.0)#487
28.	15219	5.0	31.0(-26.0)#28	32.0(-27.0)#495
29.	15963	5.0	31.0(-26.0)#29	32.0(-27.0)#497
30.	18032	5.0	31.0(-26.0)#30	32.0(-27.0)#502
31.	18708	5.0	31.0(-26.0)#31	32.0(-27.0)#505
32.	17810	5.0	31.0(-26.0)#32	32.0(-27.0)#524
33.	18661	5.0	31.0(-26.0)#33	32.0(-27.0)#531
34.	17814	5.0	31.0(-26.0)#34	32.0(-27.0)#538
35.	18232	5.0	31.0(-26.0)#35	32.0(-27.0)#545
36.	17045	5.0	31.0(-26.0)#36	32.0(-27.0)#551
37.	15545	5.0	31.0(-26.0)#37	32.0(-27.0)#558
38.	19134	6.0	31.0(-25.0)#38	32.0(-26.0)#579
39.	18201	6.0	31.0(-25.0)#39	32.0(-26.0)#601
40.	15210	6.0	31.0(-25.0)#40	32.0(-26.0)#621
41.	18504	6.0	31.0(-25.0)#41	32.0(-26.0)#644
42.	15904	6.0	31.0(-25.0)#42	32.0(-26.0)#667
43.	18444	6.0	31.0(-25.0)#43	32.0(-26.0)#676
44.	18031	6.0	31.0(-25.0)#44	32.0(-26.0)#688
45.	17844	6.0	31.0(-25.0)#45	32.0(-26.0)#709
46.	15478	6.0	31.0(-25.0)#46	32.0(-26.0)#737
47.	15530	6.0	31.0(-25.0)#47	32.0(-26.0)#743
48.	17301	6.0	31.0(-25.0)#48	32.0(-26.0)#748
49.	15314	6.0	31.0(-25.0)#49	32.0(-26.0)#756
50.	17315	7.0	31.0(-24.0)#50	32.0(-25.0)#814
51.	17801	7.0	31.0(-24.0)#51	32.0(-25.0)#863
52.	15209	7.0	31.0(-24.0)#52	32.0(-25.0)#890
53.	18071	7.0	31.0(-24.0)#53	32.0(-25.0)#895
54.	17751	7.0	31.0(-24.0)#54	32.0(-25.0)#921
55.	15021	7.0	31.0(-24.0)#55	32.0(-25.0)#926
56.	19074	7.0	31.0(-24.0)#56	32.0(-25.0)#931
57.	16025	7.0	31.0(-24.0)#57	32.0(-25.0)#942
58.	16828	7.0	31.0(-24.0)#58	32.0(-25.0)#943
59.	15541	7.0	31.0(-24.0)#59	32.0(-25.0)#964
60.	16248	7.0	31.0(-24.0)#60	32.0(-25.0)#968
61.	16049	7.0	31.0(-24.0)#61	32.0(-25.0)#972
62.	17774	7.0	31.0(-24.0)#62	32.0(-25.0)#996
63.	19464	8.0	31.0(-23.0)#63	32.0(-24.0)#1,005
64.	17022	8.0	31.0(-23.0)#64	32.0(-24.0)#1,043
65.	15401	8.0	31.0(-23.0)#65	32.0(-24.0)#1,051
66.	17036	8.0	31.0(-23.0)#66	32.0(-24.0)#1,080
67.	16125	8.0	31.0(-23.0)#67	32.0(-24.0)#1,098
68.	16505	8.0	31.0(-23.0)#68	32.0(-24.0)#1,108
69.	16105	8.0	31.0(-23.0)#69	32.0(-24.0)#1,116
70.	16301	8.0	31.0(-23.0)#70	32.0(-24.0)#1,119
71.	18407	8.0	31.0(-23.0)#71	32.0(-24.0)#1,124
72.	17756	8.0	31.0(-23.0)#72	32.0(-24.0)#1,141
73.	19526	8.0	31.0(-23.0)#73	32.0(-24.0)#1,153
74.	15224	8.0	31.0(-23.0)#74	32.0(-24.0)#1,155
75.	16354	8.0	31.0(-23.0)#75	32.0(-24.0)#1,163
76.	15137	8.0	31.0(-23.0)#76	32.0(-24.0)#1,164
77.	17963	8.0	31.0(-23.0)#77	32.0(-24.0)#1,169
78.	16214	8.0	31.0(-23.0)#78	32.0(-24.0)#1,174
79.	17931	8.0	31.0(-23.0)#79	32.0(-24.0)#1,177
80.	15139	8.0	31.0(-23.0)#80	32.0(-24.0)#1,192
81.	18925	8.0	31.0(-23.0)#81	32.0(-24.0)#1,195
82.	16735	8.0	31.0(-23.0)#82	32.0(-24.0)#1,196
83.	16630	8.0	31.0(-23.0)#83	32.0(-24.0)#1,217
84.	17240	8.0	31.0(-23.0)#84	32.0(-24.0)#1,238
85.	17744	8.0	31.0(-23.0)#85	32.0(-24.0)#1,246
86.	16041	8.0	31.0(-23.0)#86	32.0(-24.0)#1,258
87.	17402	9.0	31.0(-22.0)#87	32.0(-23.0)#1,295
88.	17512	9.0	31.0(-22.0)#88	32.0(-23.0)#1,363
89.	16365	9.0	31.0(-22.0)#89	32.0(-23.0)#1,368
90.	18040	9.0	31.0(-22.0)#90	32.0(-23.0)#1,370
91.	16701	9.0	31.0(-22.0)#91	32.0(-23.0)#1,374
92.	19015	9.0	31.0(-22.0)#92	32.0(-23.0)#1,379
93.	18508	9.0	31.0(-22.0)#93	32.0(-23.0)#1,403
94.	15656	9.0	31.0(-22.0)#94	32.0(-23.0)#1,420
95.	18072	9.0	31.0(-22.0)#95	32.0(-23.0)#1,447
96.	16743	9.0	31.0(-22.0)#96	32.0(-23.0)#1,471
97.	16875	9.0	31.0(-22.0)#97	32.0(-23.0)#1,480
98.	17853	9.0	31.0(-22.0)#98	32.0(-23.0)#1,494
99.	16101	10.0	31.0(-21.0)#99	32.0(-22.0)#1,597
100.	19126	10.0	31.0(-21.0)#100	32.0(-22.0)#1,649

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Common Questions

What are the Top 10 Zip Codes with the Fewest Births per 1,000 Women Over the Age of 35 in Pennsylvania?

Top 10 Zip Codes with the Fewest Births per 1,000 Women Over the Age of 35 in Pennsylvania are:

1.0

1.0

1.0

2.0

2.0

2.0

2.0

2.0

3.0

#10

17046

3.0

What zip code has the Fewest Births per 1,000 Women Over the Age of 35 in Pennsylvania?

19061 has the Fewest Births per 1,000 Women Over the Age of 35 in Pennsylvania with 1.0.

What is the Number of Births per 1,000 Women Over the Age of 35 in the State of Pennsylvania?

Number of Births per 1,000 Women Over the Age of 35 in Pennsylvania is 31.0.

What is the Number of Births per 1,000 Women Over the Age of 35 in the United States?

Number of Births per 1,000 Women Over the Age of 35 in the United States is 32.0.