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D

Persons Arrested By Sex, According To Residential Status And Broad Age Group, Annual

Description

Annual counts of persons arrested in Singapore from 2011 through 2025 by sex, residential status, and broad age group, from the Singapore Police Force. Crime statisticians analyse arrest profiles across demographic groups. Adapted from SingStat TableBuilder TS/M890881.

Official description

Source: SINGAPORE POLICE FORCE Data Last Updated: 20/02/2026 Update Frequency: Annual Adapted from: https://tablebuilder.singstat.gov.sg/table/TS/M890881

Last updated
Coverage
2011-01-01 – 2025-12-31
Rows
26
Columns
16

Chart

Values are summed where multiple rows share the same category.

Data

Data Series 2025 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 2011
Total Persons Arrested 23580.000000 15454 15605 15618 18059 15079 17146 17220 16636 17005 16929 17687 17002 18249 18561
Male 17303.000000 11405 11612 11746 13639 11542 13128 13171 12777 12991 13097 14066 13598 14275 14444
Female 6259.000000 4030 3984 3857 4411 3537 4018 4049 3859 4014 3832 3621 3404 3974 4117
Unknown Gender 18.000000 19 9 15 9 na na na na na na na na na na
Singaporeans/ Permanent Residents/ Stateless 17033.000000 10833 10883 11053 13866 11981 12641 12731 12231 12664 12693 13403 12984 14390 14668
Male 12689.000000 8189 8295 8519 10669 9321 9920 10021 9616 9854 10003 10866 10604 11505 11676
Female 4343.000000 2644 2587 2525 3194 2660 2721 2710 2615 2810 2690 2537 2380 2885 2992
Unknown Gender 1.000000 na 1 9 3 na na na na na na na na na na
Foreigners 6443.000000 4565 4697 4548 4186 3098 4505 4489 4405 4341 4236 4284 4018 3859 3893
Male 4545.000000 3185 3301 3217 2970 2221 3208 3150 3161 3137 3094 3200 2994 2770 2768
Female 1889.000000 1373 1391 1329 1216 877 1297 1339 1244 1204 1142 1084 1024 1089 1125
Unknown Gender 9.000000 7 5 2 na na na na na na na na na na na
Unknown Residential Status 104.000000 56 25 17 7 na na na na na na na na na na
Above 21 Years Old 18753.000000 12379 12584 12832 14673 11911 13692 13738 13047 13420 12844 13820 13198 14105 14280
Male 13705.000000 9105 9328 9623 10992 8997 10465 10479 10041 10294 9886 11061 10648 11061 11171
Female 5042.000000 3272 3251 3208 3681 2914 3227 3259 3006 3126 2958 2759 2550 3044 3109
Unknown Gender 6.000000 2 5 1 na na na na na na na na na na na
21 Years Old And Below 4792.000000 3045 3008 2764 3377 3168 3454 3482 3589 3585 4085 3867 3804 4144 4281
Male 3582.000000 2291 2280 2115 2647 2545 2663 2692 2736 2697 3211 3005 2950 3214 3273
Female 1209.000000 754 728 649 730 623 791 790 853 888 874 862 854 930 1008
Unknown Gender 1.000000 na na na na na na na na na na na na na na
Youths (7 To 19 Years Old) 3570.000000 2269 2288 2023 2575 2422 2699 2703 2795 2788 3265 3120 3031 3359 3477
Male 2668.000000 1686 1716 1536 2037 1959 2077 2103 2124 2098 2553 2435 2356 2638 2677
Female 901.000000 583 572 487 538 463 622 600 671 690 712 685 675 721 800
Unknown Gender 1.000000 na na na na na na na na na na na na na na

Columns

Column Type Categorical
Data Series Text No
2025 Numeric No
2024 Text No
2023 Text No
2022 Text No
2021 Text No
2020 Text No
2019 Text No
2018 Text No
2017 Text No
2016 Text No
2015 Text No
2014 Text No
2013 Text No
2012 Text No
2011 Text No