Immigrants from Bangladesh vs Kenyan Community Comparison

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Immigrants from Bangladesh
Race
Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican 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
Kenyan
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 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
NonimmigrantsImmigrantsAfghanistanAfricaAlbaniaArgentinaArmeniaAsiaAustraliaAustriaBahamasBarbadosBelarusBelgiumBelizeBoliviaBosnia 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

Immigrants from Bangladesh

Kenyans

Poor
Good
2,108
SOCIAL INDEX
18.6/ 100
SOCIAL RATING
269th/ 347
SOCIAL RANK
6,922
SOCIAL INDEX
66.7/ 100
SOCIAL RATING
135th/ 347
SOCIAL RANK

Kenyan Integration in Immigrants from Bangladesh Communities

The statistical analysis conducted on geographies consisting of 112,551,615 people shows a poor positive correlation between the proportion of Kenyans within Immigrant from Bangladesh communities in the United States with a correlation coefficient (R) of 0.149. On average, for every 1% (one percent) increase in Immigrants from Bangladesh within a typical geography, there is an increase of 0.003% in Kenyans. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Immigrants from Bangladesh corresponds to an increase of 3.4 Kenyans.
Immigrants from Bangladesh Integration in Kenyan Communities

Immigrants from Bangladesh vs Kenyan Income

When considering income, the most significant differences between Immigrants from Bangladesh and Kenyan communities in the United States are seen in wage/income gap (20.9% compared to 24.5%, a difference of 16.8%), householder income over 65 years ($55,394 compared to $60,514, a difference of 9.2%), and householder income under 25 years ($54,714 compared to $50,815, a difference of 7.7%). Conversely, both communities are more comparable in terms of median female earnings ($39,910 compared to $39,860, a difference of 0.12%), householder income ages 25 - 44 years ($90,448 compared to $91,684, a difference of 1.4%), and median earnings ($45,532 compared to $46,462, a difference of 2.0%).
Immigrants from Bangladesh vs Kenyan Income
Income MetricImmigrants from BangladeshKenyan
Per Capita Income
Poor
$41,709
Fair
$42,808
Median Family Income
Tragic
$94,665
Fair
$101,417
Median Household Income
Tragic
$80,722
Fair
$84,085
Median Earnings
Fair
$45,532
Average
$46,462
Median Male Earnings
Tragic
$51,642
Fair
$53,647
Median Female Earnings
Good
$39,910
Average
$39,860
Householder Age | Under 25 years
Exceptional
$54,714
Tragic
$50,815
Householder Age | 25 - 44 years
Tragic
$90,448
Poor
$91,684
Householder Age | 45 - 64 years
Tragic
$92,208
Fair
$98,970
Householder Age | Over 65 years
Tragic
$55,394
Fair
$60,514
Wage/Income Gap
Exceptional
20.9%
Exceptional
24.5%

Immigrants from Bangladesh vs Kenyan Poverty

When considering poverty, the most significant differences between Immigrants from Bangladesh and Kenyan communities in the United States are seen in married-couple family poverty (7.5% compared to 4.8%, a difference of 56.5%), receiving food stamps (15.9% compared to 11.6%, a difference of 37.5%), and seniors poverty over the age of 75 (15.8% compared to 11.5%, a difference of 37.2%). Conversely, both communities are more comparable in terms of single male poverty (13.0% compared to 12.4%, a difference of 5.4%), single father poverty (16.3% compared to 15.3%, a difference of 6.1%), and single female poverty (22.3% compared to 20.8%, a difference of 7.5%).
Immigrants from Bangladesh vs Kenyan Poverty
Poverty MetricImmigrants from BangladeshKenyan
Poverty
Tragic
15.3%
Fair
12.5%
Families
Tragic
11.7%
Average
8.9%
Males
Tragic
14.1%
Fair
11.3%
Females
Tragic
16.4%
Average
13.5%
Females 18 to 24 years
Tragic
21.8%
Average
20.2%
Females 25 to 34 years
Tragic
14.8%
Average
13.5%
Children Under 5 years
Tragic
20.1%
Fair
17.5%
Children Under 16 years
Tragic
19.8%
Fair
16.5%
Boys Under 16 years
Tragic
19.9%
Average
16.6%
Girls Under 16 years
Tragic
19.9%
Fair
16.8%
Single Males
Fair
13.0%
Exceptional
12.4%
Single Females
Tragic
22.3%
Good
20.8%
Single Fathers
Average
16.3%
Exceptional
15.3%
Single Mothers
Tragic
31.1%
Exceptional
28.4%
Married Couples
Tragic
7.5%
Exceptional
4.8%
Seniors Over 65 years
Tragic
14.1%
Exceptional
10.3%
Seniors Over 75 years
Tragic
15.8%
Exceptional
11.5%
Receiving Food Stamps
Tragic
15.9%
Good
11.6%

Immigrants from Bangladesh vs Kenyan Unemployment

When considering unemployment, the most significant differences between Immigrants from Bangladesh and Kenyan communities in the United States are seen in unemployment among ages 16 to 19 years (21.5% compared to 16.1%, a difference of 33.8%), unemployment among ages 55 to 59 years (5.9% compared to 4.4%, a difference of 32.6%), and unemployment among ages 60 to 64 years (6.0% compared to 4.6%, a difference of 30.3%). Conversely, both communities are more comparable in terms of unemployment among seniors over 75 years (9.1% compared to 9.1%, a difference of 0.11%), unemployment among women with children ages 6 to 17 years (8.8% compared to 8.8%, a difference of 0.49%), and unemployment among women with children under 6 years (8.8% compared to 7.6%, a difference of 16.5%).
Immigrants from Bangladesh vs Kenyan Unemployment
Unemployment MetricImmigrants from BangladeshKenyan
Unemployment
Tragic
6.5%
Excellent
5.1%
Males
Tragic
6.6%
Good
5.2%
Females
Tragic
6.5%
Exceptional
5.0%
Youth < 25
Tragic
14.2%
Exceptional
11.2%
Age | 16 to 19 years
Tragic
21.5%
Exceptional
16.1%
Age | 20 to 24 years
Tragic
12.6%
Exceptional
9.9%
Age | 25 to 29 years
Tragic
7.5%
Exceptional
6.3%
Age | 30 to 34 years
Tragic
6.4%
Exceptional
5.2%
Age | 35 to 44 years
Tragic
5.3%
Exceptional
4.4%
Age | 45 to 54 years
Tragic
5.4%
Exceptional
4.3%
Age | 55 to 59 years
Tragic
5.9%
Exceptional
4.4%
Age | 60 to 64 years
Tragic
6.0%
Exceptional
4.6%
Age | 65 to 74 years
Tragic
5.9%
Exceptional
4.8%
Seniors > 65
Tragic
5.7%
Exceptional
4.7%
Seniors > 75
Tragic
9.1%
Tragic
9.1%
Women w/ Children < 6
Tragic
8.8%
Good
7.6%
Women w/ Children 6 to 17
Good
8.8%
Excellent
8.8%
Women w/ Children < 18
Tragic
6.4%
Excellent
5.3%

Immigrants from Bangladesh vs Kenyan Labor Participation

When considering labor participation, the most significant differences between Immigrants from Bangladesh and Kenyan communities in the United States are seen in in labor force | age 16-19 (30.0% compared to 40.1%, a difference of 33.6%), in labor force | age 20-24 (70.6% compared to 77.0%, a difference of 9.0%), and in labor force | age > 16 (64.5% compared to 67.6%, a difference of 4.8%). Conversely, both communities are more comparable in terms of in labor force | age 30-34 (83.6% compared to 85.4%, a difference of 2.2%), in labor force | age 35-44 (82.9% compared to 85.2%, a difference of 2.8%), and in labor force | age 25-29 (83.0% compared to 85.4%, a difference of 2.9%).
Immigrants from Bangladesh vs Kenyan Labor Participation
Labor Participation MetricImmigrants from BangladeshKenyan
In Labor Force | Age > 16
Tragic
64.5%
Exceptional
67.6%
In Labor Force | Age 20-64
Tragic
77.9%
Exceptional
80.8%
In Labor Force | Age 16-19
Tragic
30.0%
Exceptional
40.1%
In Labor Force | Age 20-24
Tragic
70.6%
Exceptional
77.0%
In Labor Force | Age 25-29
Tragic
83.0%
Exceptional
85.4%
In Labor Force | Age 30-34
Tragic
83.6%
Exceptional
85.4%
In Labor Force | Age 35-44
Tragic
82.9%
Exceptional
85.2%
In Labor Force | Age 45-54
Tragic
80.7%
Exceptional
83.7%

Immigrants from Bangladesh vs Kenyan Family Structure

When considering family structure, the most significant differences between Immigrants from Bangladesh and Kenyan communities in the United States are seen in single father households (2.1% compared to 2.4%, a difference of 14.9%), divorced or separated (11.0% compared to 12.2%, a difference of 11.2%), and average family size (3.36 compared to 3.21, a difference of 4.6%). Conversely, both communities are more comparable in terms of family households (63.9% compared to 63.2%, a difference of 1.1%), single mother households (6.9% compared to 7.0%, a difference of 1.3%), and family households with children (27.6% compared to 28.4%, a difference of 3.0%).
Immigrants from Bangladesh vs Kenyan Family Structure
Family Structure MetricImmigrants from BangladeshKenyan
Family Households
Poor
63.9%
Tragic
63.2%
Family Households with Children
Good
27.6%
Exceptional
28.4%
Married-couple Households
Tragic
43.1%
Tragic
44.7%
Average Family Size
Exceptional
3.36
Fair
3.21
Single Father Households
Exceptional
2.1%
Fair
2.4%
Single Mother Households
Tragic
6.9%
Tragic
7.0%
Currently Married
Tragic
43.6%
Tragic
45.2%
Divorced or Separated
Exceptional
11.0%
Fair
12.2%
Births to Unmarried Women
Good
30.9%
Average
31.9%

Immigrants from Bangladesh vs Kenyan Vehicle Availability

When considering vehicle availability, the most significant differences between Immigrants from Bangladesh and Kenyan communities in the United States are seen in no vehicles in household (25.8% compared to 9.7%, a difference of 165.4%), 4 or more vehicles in household (3.9% compared to 6.1%, a difference of 56.2%), and 3 or more vehicles in household (12.5% compared to 19.1%, a difference of 52.5%). Conversely, both communities are more comparable in terms of 1 or more vehicles in household (74.3% compared to 90.4%, a difference of 21.6%), 2 or more vehicles in household (38.8% compared to 55.5%, a difference of 43.2%), and 3 or more vehicles in household (12.5% compared to 19.1%, a difference of 52.5%).
Immigrants from Bangladesh vs Kenyan Vehicle Availability
Vehicle Availability MetricImmigrants from BangladeshKenyan
No Vehicles Available
Tragic
25.8%
Excellent
9.7%
1+ Vehicles Available
Tragic
74.3%
Excellent
90.4%
2+ Vehicles Available
Tragic
38.8%
Average
55.5%
3+ Vehicles Available
Tragic
12.5%
Fair
19.1%
4+ Vehicles Available
Tragic
3.9%
Poor
6.1%

Immigrants from Bangladesh vs Kenyan Education Level

When considering education level, the most significant differences between Immigrants from Bangladesh and Kenyan communities in the United States are seen in no schooling completed (3.1% compared to 2.0%, a difference of 53.8%), college, under 1 year (61.3% compared to 66.5%, a difference of 8.5%), and college, 1 year or more (56.6% compared to 60.5%, a difference of 6.9%). Conversely, both communities are more comparable in terms of professional degree (4.4% compared to 4.4%, a difference of 0.87%), master's degree (15.5% compared to 15.3%, a difference of 0.92%), and nursery school (96.9% compared to 98.0%, a difference of 1.1%).
Immigrants from Bangladesh vs Kenyan Education Level
Education Level MetricImmigrants from BangladeshKenyan
No Schooling Completed
Tragic
3.1%
Good
2.0%
Nursery School
Tragic
96.9%
Average
98.0%
Kindergarten
Tragic
96.8%
Average
98.0%
1st Grade
Tragic
96.8%
Average
97.9%
2nd Grade
Tragic
96.7%
Average
97.9%
3rd Grade
Tragic
96.6%
Average
97.8%
4th Grade
Tragic
96.2%
Average
97.5%
5th Grade
Tragic
96.0%
Average
97.4%
6th Grade
Tragic
95.4%
Good
97.1%
7th Grade
Tragic
94.0%
Good
96.2%
8th Grade
Tragic
93.6%
Good
95.9%
9th Grade
Tragic
92.4%
Good
95.1%
10th Grade
Tragic
91.0%
Good
94.0%
11th Grade
Tragic
89.5%
Excellent
92.9%
12th Grade, No Diploma
Tragic
88.0%
Good
91.5%
High School Diploma
Tragic
85.5%
Excellent
89.6%
GED/Equivalency
Tragic
81.9%
Good
86.3%
College, Under 1 year
Tragic
61.3%
Excellent
66.5%
College, 1 year or more
Tragic
56.6%
Good
60.5%
Associate's Degree
Fair
45.2%
Good
47.1%
Bachelor's Degree
Average
37.8%
Good
38.7%
Master's Degree
Good
15.5%
Good
15.3%
Professional Degree
Average
4.4%
Average
4.4%
Doctorate Degree
Average
1.8%
Excellent
1.9%

Immigrants from Bangladesh vs Kenyan Disability

When considering disability, the most significant differences between Immigrants from Bangladesh and Kenyan communities in the United States are seen in disability age under 5 (0.85% compared to 1.2%, a difference of 41.6%), disability age 18 to 34 (5.6% compared to 6.8%, a difference of 20.1%), and hearing disability (2.4% compared to 2.8%, a difference of 17.2%). Conversely, both communities are more comparable in terms of disability age 65 to 74 (23.6% compared to 23.7%, a difference of 0.52%), female disability (11.8% compared to 11.9%, a difference of 0.93%), and cognitive disability (17.8% compared to 18.1%, a difference of 1.6%).
Immigrants from Bangladesh vs Kenyan Disability
Disability MetricImmigrants from BangladeshKenyan
Disability
Exceptional
11.0%
Excellent
11.5%
Males
Exceptional
10.3%
Good
11.0%
Females
Exceptional
11.8%
Exceptional
11.9%
Age | Under 5 years
Exceptional
0.85%
Good
1.2%
Age | 5 to 17 years
Exceptional
5.2%
Poor
5.8%
Age | 18 to 34 years
Exceptional
5.6%
Poor
6.8%
Age | 35 to 64 years
Excellent
10.9%
Fair
11.4%
Age | 65 to 74 years
Fair
23.6%
Fair
23.7%
Age | Over 75 years
Tragic
48.0%
Average
47.2%
Vision
Good
2.1%
Exceptional
2.1%
Hearing
Exceptional
2.4%
Excellent
2.8%
Cognitive
Tragic
17.8%
Tragic
18.1%
Ambulatory
Fair
6.2%
Exceptional
5.8%
Self-Care
Tragic
2.6%
Exceptional
2.3%