Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in New York

Common Questions

What are the Top 10 Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in New York?
Top 10 Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in New York are:
#1
2.0
#2
2.0
#3
2.0
#4
3.0
#5
3.0
#6
4.0
#7
4.0
#8
5.0
#9
6.0
#10
6.0
What zip code has the Fewest Births per 1,000 Women Below Poverty Level in New York?
14530 has the Fewest Births per 1,000 Women Below Poverty Level in New York with 2.0.
What is the Number of Births per 1,000 Women Below Poverty Level in the State of New York?
Number of Births per 1,000 Women Below Poverty Level in New York is 48.0.
What is the Number of Births per 1,000 Women Below Poverty Level in the United States?
Number of Births per 1,000 Women Below Poverty Level in the United States is 53.0.

Map of Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in New York

20.0
0.0
Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in New York Map

Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in New York

Zip Codes with the Fewest Births per 1,000 Women Below Poverty Level in New York Chart
Zip Code Births / 1,000 Women vs State vs National
1.145302.048.0(-46.0)#153.0(-51.0)#13
2.128332.048.0(-46.0)#253.0(-51.0)#19
3.109732.048.0(-46.0)#353.0(-51.0)#30
4.110203.048.0(-45.0)#453.0(-50.0)#56
5.121543.048.0(-45.0)#553.0(-50.0)#70
6.109304.048.0(-44.0)#653.0(-49.0)#97
7.121374.048.0(-44.0)#753.0(-49.0)#128
8.125235.048.0(-43.0)#853.0(-48.0)#193
9.119786.048.0(-42.0)#953.0(-47.0)#247
10.134766.048.0(-42.0)#1053.0(-47.0)#251
11.122107.048.0(-41.0)#1153.0(-46.0)#307
12.128287.048.0(-41.0)#1253.0(-46.0)#310
13.138307.048.0(-41.0)#1353.0(-46.0)#324
14.105487.048.0(-41.0)#1453.0(-46.0)#328
15.125207.048.0(-41.0)#1553.0(-46.0)#338
16.121387.048.0(-41.0)#1653.0(-46.0)#341
17.134247.048.0(-41.0)#1753.0(-46.0)#351
18.121557.048.0(-41.0)#1853.0(-46.0)#358
19.100198.048.0(-40.0)#1953.0(-45.0)#382
20.129868.048.0(-40.0)#2053.0(-45.0)#408
21.119448.048.0(-40.0)#2153.0(-45.0)#413
22.121668.048.0(-40.0)#2253.0(-45.0)#450
23.117679.048.0(-39.0)#2353.0(-44.0)#490
24.113639.048.0(-39.0)#2453.0(-44.0)#499
25.117199.048.0(-39.0)#2553.0(-44.0)#522
26.148219.048.0(-39.0)#2653.0(-44.0)#528
27.136169.048.0(-39.0)#2753.0(-44.0)#551
28.137979.048.0(-39.0)#2853.0(-44.0)#557
29.136079.048.0(-39.0)#2953.0(-44.0)#566
30.129579.048.0(-39.0)#3053.0(-44.0)#569
31.138019.048.0(-39.0)#3153.0(-44.0)#573
32.1003810.048.0(-38.0)#3253.0(-43.0)#602
33.1441110.048.0(-38.0)#3353.0(-43.0)#611
34.1151410.048.0(-38.0)#3453.0(-43.0)#637
35.1219610.048.0(-38.0)#3553.0(-43.0)#642
36.1210610.048.0(-38.0)#3653.0(-43.0)#668
37.1474110.048.0(-38.0)#3753.0(-43.0)#674
38.1342810.048.0(-38.0)#3853.0(-43.0)#689
39.1283710.048.0(-38.0)#3953.0(-43.0)#695
40.1218211.048.0(-37.0)#4053.0(-42.0)#728
41.1230511.048.0(-37.0)#4153.0(-42.0)#749
42.1098311.048.0(-37.0)#4253.0(-42.0)#760
43.1248711.048.0(-37.0)#4353.0(-42.0)#774
44.1420211.048.0(-37.0)#4453.0(-42.0)#775
45.1386211.048.0(-37.0)#4553.0(-42.0)#778
46.1211711.048.0(-37.0)#4653.0(-42.0)#795
47.1172411.048.0(-37.0)#4753.0(-42.0)#796
48.1292011.048.0(-37.0)#4853.0(-42.0)#810
49.1340911.048.0(-37.0)#4953.0(-42.0)#813
50.1362511.048.0(-37.0)#5053.0(-42.0)#818
51.1334311.048.0(-37.0)#5153.0(-42.0)#821
52.1291211.048.0(-37.0)#5253.0(-42.0)#823
53.1000312.048.0(-36.0)#5353.0(-41.0)#868
54.1000512.048.0(-36.0)#5453.0(-41.0)#899
55.1057912.048.0(-36.0)#5553.0(-41.0)#901
56.1178912.048.0(-36.0)#5653.0(-41.0)#905
57.1205712.048.0(-36.0)#5753.0(-41.0)#954
58.1474712.048.0(-36.0)#5853.0(-41.0)#955
59.1373612.048.0(-36.0)#5953.0(-41.0)#960
60.1343112.048.0(-36.0)#6053.0(-41.0)#967
61.1380212.048.0(-36.0)#6153.0(-41.0)#982
62.1483612.048.0(-36.0)#6253.0(-41.0)#986
63.1484612.048.0(-36.0)#6353.0(-41.0)#990
64.1123613.048.0(-35.0)#6453.0(-40.0)#1,006
65.1410313.048.0(-35.0)#6553.0(-40.0)#1,035
66.1334013.048.0(-35.0)#6653.0(-40.0)#1,042
67.1308413.048.0(-35.0)#6753.0(-40.0)#1,072
68.1482213.048.0(-35.0)#6853.0(-40.0)#1,136
69.1172614.048.0(-34.0)#6953.0(-39.0)#1,160
70.1303214.048.0(-34.0)#7053.0(-39.0)#1,177
71.1403114.048.0(-34.0)#7153.0(-39.0)#1,187
72.1193314.048.0(-34.0)#7253.0(-39.0)#1,202
73.1281614.048.0(-34.0)#7353.0(-39.0)#1,225
74.1214814.048.0(-34.0)#7453.0(-39.0)#1,227
75.1314014.048.0(-34.0)#7553.0(-39.0)#1,229
76.1308014.048.0(-34.0)#7653.0(-39.0)#1,239
77.1207414.048.0(-34.0)#7753.0(-39.0)#1,250
78.1207514.048.0(-34.0)#7853.0(-39.0)#1,251
79.1417014.048.0(-34.0)#7953.0(-39.0)#1,257
80.1447614.048.0(-34.0)#8053.0(-39.0)#1,258
81.1051114.048.0(-34.0)#8153.0(-39.0)#1,261
82.1405414.048.0(-34.0)#8253.0(-39.0)#1,274
83.1480314.048.0(-34.0)#8353.0(-39.0)#1,276
84.1412914.048.0(-34.0)#8453.0(-39.0)#1,280
85.1312214.048.0(-34.0)#8553.0(-39.0)#1,283
86.1486114.048.0(-34.0)#8653.0(-39.0)#1,285
87.1154515.048.0(-33.0)#8753.0(-38.0)#1,356
88.1335015.048.0(-33.0)#8853.0(-38.0)#1,362
89.1257215.048.0(-33.0)#8953.0(-38.0)#1,367
90.1200915.048.0(-33.0)#9053.0(-38.0)#1,370
91.1202515.048.0(-33.0)#9153.0(-38.0)#1,384
92.1478715.048.0(-33.0)#9253.0(-38.0)#1,390
93.1400815.048.0(-33.0)#9353.0(-38.0)#1,427
94.1293515.048.0(-33.0)#9453.0(-38.0)#1,434
95.1365915.048.0(-33.0)#9553.0(-38.0)#1,473
96.1455916.048.0(-32.0)#9653.0(-37.0)#1,492
97.1288516.048.0(-32.0)#9753.0(-37.0)#1,548
98.1420316.048.0(-32.0)#9853.0(-37.0)#1,579
99.1305216.048.0(-32.0)#9953.0(-37.0)#1,581
100.1362216.048.0(-32.0)#10053.0(-37.0)#1,586