Bangladeshi vs Northern European Community Comparison

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Bangladeshi
Race
Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorwegianOkinawanOsageOttawaPaiutePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanPuget Sound SalishRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianShoshoneSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSoviet UnionSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianTaiwaneseThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanUteVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
Immigration
NonimmigrantsImmigrantsAfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma/MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth AmericaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabweAzores
Northern European
Race
Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican American IndianMongolianMoroccanNative HawaiianNavajoNepaleseNew ZealanderNicaraguanNigerianNorthern EuropeanNorwegianOkinawanOsageOttawaPaiutePakistaniPalestinianPanamanianParaguayanPennsylvania GermanPeruvianPimaPolishPortuguesePotawatomiPuebloPuerto RicanPuget Sound SalishRomanianRussianSalvadoranSamoanScandinavianScotch-IrishScottishSeminoleSenegaleseSerbianShoshoneSierra LeoneanSiouxSlavicSlovakSloveneSomaliSouth AfricanSouth AmericanSouth American IndianSoviet UnionSpaniardSpanishSpanish AmericanSpanish American IndianSri LankanSubsaharan AfricanSudaneseSwedishSwissSyrianTaiwaneseThaiTlingit-HaidaTohono O'OdhamTonganTrinidadian and TobagonianTsimshianTurkishU.S. Virgin IslanderUgandanUkrainianUruguayanUteVenezuelanVietnameseWelshWest IndianYakamaYaquiYugoslavianYumanYup'ikZimbabwean
Immigration
NonimmigrantsImmigrantsAfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBangladeshBarbadosBelarusBelgiumBelizeBoliviaBosnia and HerzegovinaBrazilBulgariaBurma/MyanmarCabo VerdeCambodiaCameroonCanadaCaribbeanCentral AmericaChileChinaColombiaCongoCosta RicaCroatiaCubaCzechoslovakiaDenmarkDominicaDominican RepublicEastern AfricaEastern AsiaEastern EuropeEcuadorEgyptEl SalvadorEnglandEritreaEthiopiaEuropeFijiFranceGermanyGhanaGreeceGrenadaGuatemalaGuyanaHaitiHondurasHong KongHungaryIndiaIndonesiaIranIraqIrelandIsraelItalyJamaicaJapanJordanKazakhstanKenyaKoreaKuwaitLaosLatin AmericaLatviaLebanonLiberiaLithuaniaMalaysiaMexicoMicronesiaMiddle AfricaMoldovaMoroccoNepalNetherlandsNicaraguaNigeriaNorth AmericaNorth MacedoniaNorthern AfricaNorthern EuropeNorwayOceaniaPakistanPanamaPeruPhilippinesPolandPortugalRomaniaRussiaSaudi ArabiaScotlandSenegalSerbiaSierra LeoneSingaporeSomaliaSouth AfricaSouth AmericaSouth Central AsiaSouth Eastern AsiaSouthern EuropeSpainSri LankaSt. Vincent and the GrenadinesSudanSwedenSwitzerlandSyriaTaiwanThailandTrinidad and TobagoTurkeyUgandaUkraineUruguayUzbekistanVenezuelaVietnamWest IndiesWestern AfricaWestern AsiaWestern EuropeYemenZaireZimbabweAzores
Social Comparison
Social Comparison
Income
Poverty
Unemployment
Labor Participation
Family Structure
Vehicle Availability
Education Level
Disability

Social Comparison

Bangladeshis

Northern Europeans

Fair
Excellent
2,611
SOCIAL INDEX
23.6/ 100
SOCIAL RATING
249th/ 347
SOCIAL RANK
8,451
SOCIAL INDEX
82.0/ 100
SOCIAL RATING
71st/ 347
SOCIAL RANK

Northern European Integration in Bangladeshi Communities

The statistical analysis conducted on geographies consisting of 130,923,835 people shows a poor negative correlation between the proportion of Northern Europeans within Bangladeshi communities in the United States with a correlation coefficient (R) of -0.172. On average, for every 1% (one percent) increase in Bangladeshis within a typical geography, there is a decrease of 0.003% in Northern Europeans. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Bangladeshis corresponds to a decrease of 2.8 Northern Europeans.
Bangladeshi Integration in Northern European Communities

Bangladeshi vs Northern European Income

When considering income, the most significant differences between Bangladeshi and Northern European communities in the United States are seen in per capita income ($35,897 compared to $47,698, a difference of 32.9%), wage/income gap (22.2% compared to 28.3%, a difference of 27.6%), and median male earnings ($46,744 compared to $58,588, a difference of 25.3%). Conversely, both communities are more comparable in terms of householder income under 25 years ($47,589 compared to $51,678, a difference of 8.6%), median female earnings ($35,960 compared to $40,491, a difference of 12.6%), and householder income over 65 years ($54,719 compared to $64,658, a difference of 18.2%).
Bangladeshi vs Northern European Income
Income MetricBangladeshiNorthern European
Per Capita Income
Tragic
$35,897
Exceptional
$47,698
Median Family Income
Tragic
$88,358
Exceptional
$110,635
Median Household Income
Tragic
$74,112
Exceptional
$90,446
Median Earnings
Tragic
$41,263
Exceptional
$48,887
Median Male Earnings
Tragic
$46,744
Exceptional
$58,588
Median Female Earnings
Tragic
$35,960
Excellent
$40,491
Householder Age | Under 25 years
Tragic
$47,589
Fair
$51,678
Householder Age | 25 - 44 years
Tragic
$81,363
Exceptional
$100,457
Householder Age | 45 - 64 years
Tragic
$86,402
Exceptional
$107,870
Householder Age | Over 65 years
Tragic
$54,719
Exceptional
$64,658
Wage/Income Gap
Exceptional
22.2%
Tragic
28.3%

Bangladeshi vs Northern European Poverty

When considering poverty, the most significant differences between Bangladeshi and Northern European communities in the United States are seen in receiving food stamps (15.0% compared to 9.8%, a difference of 52.9%), married-couple family poverty (6.0% compared to 4.3%, a difference of 41.0%), and family poverty (10.9% compared to 7.8%, a difference of 39.4%). Conversely, both communities are more comparable in terms of single male poverty (13.3% compared to 13.0%, a difference of 2.3%), single father poverty (15.2% compared to 16.3%, a difference of 7.1%), and female poverty among 18-24 year olds (22.5% compared to 20.6%, a difference of 9.0%).
Bangladeshi vs Northern European Poverty
Poverty MetricBangladeshiNorthern European
Poverty
Tragic
14.8%
Exceptional
11.4%
Families
Tragic
10.9%
Exceptional
7.8%
Males
Tragic
13.6%
Exceptional
10.4%
Females
Tragic
16.0%
Exceptional
12.4%
Females 18 to 24 years
Tragic
22.5%
Poor
20.6%
Females 25 to 34 years
Tragic
15.9%
Good
13.2%
Children Under 5 years
Tragic
20.6%
Exceptional
16.0%
Children Under 16 years
Tragic
19.9%
Exceptional
14.5%
Boys Under 16 years
Tragic
20.0%
Exceptional
14.8%
Girls Under 16 years
Tragic
20.0%
Exceptional
14.8%
Single Males
Tragic
13.3%
Poor
13.0%
Single Females
Tragic
24.2%
Good
20.8%
Single Fathers
Exceptional
15.2%
Average
16.3%
Single Mothers
Tragic
31.7%
Excellent
28.6%
Married Couples
Tragic
6.0%
Exceptional
4.3%
Seniors Over 65 years
Fair
11.2%
Exceptional
9.4%
Seniors Over 75 years
Good
12.0%
Exceptional
10.7%
Receiving Food Stamps
Tragic
15.0%
Exceptional
9.8%

Bangladeshi vs Northern European Unemployment

When considering unemployment, the most significant differences between Bangladeshi and Northern European communities in the United States are seen in unemployment among women with children ages 6 to 17 years (7.4% compared to 8.8%, a difference of 19.1%), male unemployment (5.7% compared to 4.9%, a difference of 15.4%), and unemployment (5.4% compared to 4.8%, a difference of 13.1%). Conversely, both communities are more comparable in terms of unemployment among women with children under 6 years (7.5% compared to 7.5%, a difference of 0.040%), unemployment among ages 20 to 24 years (10.0% compared to 10.1%, a difference of 0.86%), and unemployment among ages 30 to 34 years (5.3% compared to 5.3%, a difference of 1.4%).
Bangladeshi vs Northern European Unemployment
Unemployment MetricBangladeshiNorthern European
Unemployment
Poor
5.4%
Exceptional
4.8%
Males
Tragic
5.7%
Exceptional
4.9%
Females
Good
5.2%
Exceptional
4.8%
Youth < 25
Average
11.6%
Exceptional
11.2%
Age | 16 to 19 years
Exceptional
16.9%
Exceptional
16.6%
Age | 20 to 24 years
Exceptional
10.0%
Exceptional
10.1%
Age | 25 to 29 years
Average
6.6%
Good
6.5%
Age | 30 to 34 years
Good
5.3%
Excellent
5.3%
Age | 35 to 44 years
Fair
4.8%
Exceptional
4.4%
Age | 45 to 54 years
Average
4.5%
Exceptional
4.2%
Age | 55 to 59 years
Exceptional
4.7%
Exceptional
4.5%
Age | 60 to 64 years
Exceptional
4.6%
Exceptional
4.6%
Age | 65 to 74 years
Good
5.3%
Exceptional
5.2%
Seniors > 65
Fair
5.2%
Exceptional
4.9%
Seniors > 75
Tragic
9.6%
Tragic
9.1%
Women w/ Children < 6
Good
7.5%
Good
7.5%
Women w/ Children 6 to 17
Exceptional
7.4%
Excellent
8.8%
Women w/ Children < 18
Good
5.3%
Exceptional
5.0%

Bangladeshi vs Northern European Labor Participation

When considering labor participation, the most significant differences between Bangladeshi and Northern European communities in the United States are seen in in labor force | age 16-19 (42.5% compared to 40.2%, a difference of 5.6%), in labor force | age > 16 (65.9% compared to 64.7%, a difference of 1.9%), and in labor force | age 20-24 (78.1% compared to 76.8%, a difference of 1.8%). Conversely, both communities are more comparable in terms of in labor force | age 20-64 (79.3% compared to 79.5%, a difference of 0.20%), in labor force | age 25-29 (85.1% compared to 84.9%, a difference of 0.23%), and in labor force | age 35-44 (84.1% compared to 84.3%, a difference of 0.26%).
Bangladeshi vs Northern European Labor Participation
Labor Participation MetricBangladeshiNorthern European
In Labor Force | Age > 16
Exceptional
65.9%
Tragic
64.7%
In Labor Force | Age 20-64
Poor
79.3%
Fair
79.5%
In Labor Force | Age 16-19
Exceptional
42.5%
Exceptional
40.2%
In Labor Force | Age 20-24
Exceptional
78.1%
Exceptional
76.8%
In Labor Force | Age 25-29
Exceptional
85.1%
Excellent
84.9%
In Labor Force | Age 30-34
Tragic
84.3%
Good
84.8%
In Labor Force | Age 35-44
Poor
84.1%
Average
84.3%
In Labor Force | Age 45-54
Tragic
81.3%
Average
82.7%

Bangladeshi vs Northern European Family Structure

When considering family structure, the most significant differences between Bangladeshi and Northern European communities in the United States are seen in single mother households (8.1% compared to 5.8%, a difference of 41.4%), single father households (3.1% compared to 2.2%, a difference of 36.8%), and births to unmarried women (34.4% compared to 30.6%, a difference of 12.6%). Conversely, both communities are more comparable in terms of family households (64.3% compared to 64.1%, a difference of 0.24%), divorced or separated (12.3% compared to 12.2%, a difference of 0.33%), and average family size (3.37 compared to 3.13, a difference of 7.7%).
Bangladeshi vs Northern European Family Structure
Family Structure MetricBangladeshiNorthern European
Family Households
Average
64.3%
Fair
64.1%
Family Households with Children
Exceptional
30.1%
Poor
27.2%
Married-couple Households
Tragic
43.5%
Exceptional
48.4%
Average Family Size
Exceptional
3.37
Tragic
3.13
Single Father Households
Tragic
3.1%
Excellent
2.2%
Single Mother Households
Tragic
8.1%
Exceptional
5.8%
Currently Married
Tragic
43.7%
Exceptional
48.7%
Divorced or Separated
Poor
12.3%
Poor
12.2%
Births to Unmarried Women
Tragic
34.4%
Excellent
30.6%

Bangladeshi vs Northern European Vehicle Availability

When considering vehicle availability, the most significant differences between Bangladeshi and Northern European communities in the United States are seen in no vehicles in household (8.7% compared to 7.9%, a difference of 9.3%), 4 or more vehicles in household (7.6% compared to 7.3%, a difference of 3.6%), and 2 or more vehicles in household (58.4% compared to 59.9%, a difference of 2.4%). Conversely, both communities are more comparable in terms of 3 or more vehicles in household (21.9% compared to 22.0%, a difference of 0.63%), 1 or more vehicles in household (91.4% compared to 92.2%, a difference of 0.89%), and 2 or more vehicles in household (58.4% compared to 59.9%, a difference of 2.4%).
Bangladeshi vs Northern European Vehicle Availability
Vehicle Availability MetricBangladeshiNorthern European
No Vehicles Available
Exceptional
8.7%
Exceptional
7.9%
1+ Vehicles Available
Exceptional
91.4%
Exceptional
92.2%
2+ Vehicles Available
Exceptional
58.4%
Exceptional
59.9%
3+ Vehicles Available
Exceptional
21.9%
Exceptional
22.0%
4+ Vehicles Available
Exceptional
7.6%
Exceptional
7.3%

Bangladeshi vs Northern European Education Level

When considering education level, the most significant differences between Bangladeshi and Northern European communities in the United States are seen in no schooling completed (3.5% compared to 1.6%, a difference of 124.3%), doctorate degree (1.2% compared to 2.2%, a difference of 84.3%), and professional degree (3.1% compared to 5.2%, a difference of 68.6%). Conversely, both communities are more comparable in terms of nursery school (96.6% compared to 98.5%, a difference of 2.0%), kindergarten (96.6% compared to 98.5%, a difference of 2.0%), and 1st grade (96.5% compared to 98.5%, a difference of 2.0%).
Bangladeshi vs Northern European Education Level
Education Level MetricBangladeshiNorthern European
No Schooling Completed
Tragic
3.5%
Exceptional
1.6%
Nursery School
Tragic
96.6%
Exceptional
98.5%
Kindergarten
Tragic
96.6%
Exceptional
98.5%
1st Grade
Tragic
96.5%
Exceptional
98.5%
2nd Grade
Tragic
96.5%
Exceptional
98.4%
3rd Grade
Tragic
96.3%
Exceptional
98.3%
4th Grade
Tragic
96.1%
Exceptional
98.2%
5th Grade
Tragic
95.9%
Exceptional
98.0%
6th Grade
Tragic
95.7%
Exceptional
97.8%
7th Grade
Tragic
94.5%
Exceptional
97.1%
8th Grade
Tragic
94.3%
Exceptional
96.9%
9th Grade
Tragic
93.4%
Exceptional
96.2%
10th Grade
Tragic
92.2%
Exceptional
95.3%
11th Grade
Tragic
90.9%
Exceptional
94.2%
12th Grade, No Diploma
Tragic
89.3%
Exceptional
92.9%
High School Diploma
Tragic
86.9%
Exceptional
91.3%
GED/Equivalency
Tragic
83.1%
Exceptional
87.9%
College, Under 1 year
Tragic
61.4%
Exceptional
69.0%
College, 1 year or more
Tragic
54.5%
Exceptional
62.9%
Associate's Degree
Tragic
40.0%
Exceptional
49.5%
Bachelor's Degree
Tragic
30.2%
Exceptional
41.0%
Master's Degree
Tragic
10.5%
Exceptional
16.7%
Professional Degree
Tragic
3.1%
Exceptional
5.2%
Doctorate Degree
Tragic
1.2%
Exceptional
2.2%

Bangladeshi vs Northern European Disability

When considering disability, the most significant differences between Bangladeshi and Northern European communities in the United States are seen in disability age under 5 (1.3% compared to 1.6%, a difference of 20.5%), disability age 35 to 64 (13.6% compared to 11.4%, a difference of 19.4%), and disability age 65 to 74 (26.8% compared to 22.6%, a difference of 18.6%). Conversely, both communities are more comparable in terms of disability age 18 to 34 (7.4% compared to 7.3%, a difference of 0.83%), male disability (12.0% compared to 11.9%, a difference of 0.96%), and disability age 5 to 17 (5.8% compared to 5.7%, a difference of 1.5%).
Bangladeshi vs Northern European Disability
Disability MetricBangladeshiNorthern European
Disability
Tragic
12.6%
Tragic
12.1%
Males
Tragic
12.0%
Tragic
11.9%
Females
Tragic
13.1%
Fair
12.3%
Age | Under 5 years
Poor
1.3%
Tragic
1.6%
Age | 5 to 17 years
Tragic
5.8%
Poor
5.7%
Age | 18 to 34 years
Tragic
7.4%
Tragic
7.3%
Age | 35 to 64 years
Tragic
13.6%
Fair
11.4%
Age | 65 to 74 years
Tragic
26.8%
Excellent
22.6%
Age | Over 75 years
Tragic
49.4%
Exceptional
46.3%
Vision
Tragic
2.3%
Average
2.2%
Hearing
Tragic
3.2%
Tragic
3.4%
Cognitive
Tragic
18.6%
Exceptional
16.8%
Ambulatory
Poor
6.3%
Good
6.0%
Self-Care
Tragic
2.8%
Exceptional
2.4%