Immigrants from Bangladesh vs Peruvian Community Comparison

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Immigrants from Bangladesh
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 GermanPimaPolishPortuguesePotawatomiPuebloPuerto 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
Peruvian
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

Peruvians

Poor
Average
2,108
SOCIAL INDEX
18.6/ 100
SOCIAL RATING
269th/ 347
SOCIAL RANK
5,786
SOCIAL INDEX
55.4/ 100
SOCIAL RATING
168th/ 347
SOCIAL RANK

Peruvian Integration in Immigrants from Bangladesh Communities

The statistical analysis conducted on geographies consisting of 182,380,624 people shows a slight negative correlation between the proportion of Peruvians within Immigrant from Bangladesh communities in the United States with a correlation coefficient (R) of -0.069. On average, for every 1% (one percent) increase in Immigrants from Bangladesh within a typical geography, there is a decrease of 0.021% in Peruvians. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Immigrants from Bangladesh corresponds to a decrease of 21.1 Peruvians.
Immigrants from Bangladesh Integration in Peruvian Communities

Immigrants from Bangladesh vs Peruvian Income

When considering income, the most significant differences between Immigrants from Bangladesh and Peruvian communities in the United States are seen in wage/income gap (20.9% compared to 25.6%, a difference of 22.2%), householder income ages 45 - 64 years ($92,208 compared to $105,070, a difference of 14.0%), and householder income over 65 years ($55,394 compared to $62,766, a difference of 13.3%). Conversely, both communities are more comparable in terms of median female earnings ($39,910 compared to $40,234, a difference of 0.81%), householder income under 25 years ($54,714 compared to $56,052, a difference of 2.5%), and median earnings ($45,532 compared to $47,628, a difference of 4.6%).
Immigrants from Bangladesh vs Peruvian Income
Income MetricImmigrants from BangladeshPeruvian
Per Capita Income
Poor
$41,709
Good
$44,479
Median Family Income
Tragic
$94,665
Excellent
$105,444
Median Household Income
Tragic
$80,722
Exceptional
$90,261
Median Earnings
Fair
$45,532
Excellent
$47,628
Median Male Earnings
Tragic
$51,642
Good
$55,659
Median Female Earnings
Good
$39,910
Good
$40,234
Householder Age | Under 25 years
Exceptional
$54,714
Exceptional
$56,052
Householder Age | 25 - 44 years
Tragic
$90,448
Exceptional
$98,886
Householder Age | 45 - 64 years
Tragic
$92,208
Exceptional
$105,070
Householder Age | Over 65 years
Tragic
$55,394
Excellent
$62,766
Wage/Income Gap
Exceptional
20.9%
Good
25.6%

Immigrants from Bangladesh vs Peruvian Poverty

When considering poverty, the most significant differences between Immigrants from Bangladesh and Peruvian communities in the United States are seen in married-couple family poverty (7.5% compared to 5.3%, a difference of 41.4%), receiving food stamps (15.9% compared to 11.7%, a difference of 35.4%), and family poverty (11.7% compared to 8.8%, a difference of 33.0%). Conversely, both communities are more comparable in terms of single father poverty (16.3% compared to 15.4%, a difference of 5.4%), single male poverty (13.0% compared to 11.8%, a difference of 10.6%), and single mother poverty (31.1% compared to 27.5%, a difference of 13.2%).
Immigrants from Bangladesh vs Peruvian Poverty
Poverty MetricImmigrants from BangladeshPeruvian
Poverty
Tragic
15.3%
Excellent
11.8%
Families
Tragic
11.7%
Good
8.8%
Males
Tragic
14.1%
Excellent
10.7%
Females
Tragic
16.4%
Excellent
12.9%
Females 18 to 24 years
Tragic
21.8%
Exceptional
17.2%
Females 25 to 34 years
Tragic
14.8%
Exceptional
12.7%
Children Under 5 years
Tragic
20.1%
Exceptional
16.0%
Children Under 16 years
Tragic
19.8%
Excellent
15.3%
Boys Under 16 years
Tragic
19.9%
Excellent
15.5%
Girls Under 16 years
Tragic
19.9%
Exceptional
15.4%
Single Males
Fair
13.0%
Exceptional
11.8%
Single Females
Tragic
22.3%
Exceptional
19.4%
Single Fathers
Average
16.3%
Exceptional
15.4%
Single Mothers
Tragic
31.1%
Exceptional
27.5%
Married Couples
Tragic
7.5%
Fair
5.3%
Seniors Over 65 years
Tragic
14.1%
Tragic
11.7%
Seniors Over 75 years
Tragic
15.8%
Tragic
13.4%
Receiving Food Stamps
Tragic
15.9%
Average
11.7%

Immigrants from Bangladesh vs Peruvian Unemployment

When considering unemployment, the most significant differences between Immigrants from Bangladesh and Peruvian communities in the United States are seen in male unemployment (6.6% compared to 5.3%, a difference of 24.1%), unemployment among ages 16 to 19 years (21.5% compared to 17.7%, a difference of 21.5%), and unemployment (6.5% compared to 5.3%, a difference of 21.5%). Conversely, both communities are more comparable in terms of unemployment among seniors over 75 years (9.1% compared to 9.0%, a difference of 0.30%), unemployment among women with children ages 6 to 17 years (8.8% compared to 9.2%, a difference of 4.1%), and unemployment among ages 65 to 74 years (5.9% compared to 5.5%, a difference of 5.7%).
Immigrants from Bangladesh vs Peruvian Unemployment
Unemployment MetricImmigrants from BangladeshPeruvian
Unemployment
Tragic
6.5%
Fair
5.3%
Males
Tragic
6.6%
Average
5.3%
Females
Tragic
6.5%
Tragic
5.4%
Youth < 25
Tragic
14.2%
Poor
11.8%
Age | 16 to 19 years
Tragic
21.5%
Fair
17.7%
Age | 20 to 24 years
Tragic
12.6%
Poor
10.5%
Age | 25 to 29 years
Tragic
7.5%
Good
6.6%
Age | 30 to 34 years
Tragic
6.4%
Average
5.5%
Age | 35 to 44 years
Tragic
5.3%
Average
4.7%
Age | 45 to 54 years
Tragic
5.4%
Fair
4.6%
Age | 55 to 59 years
Tragic
5.9%
Fair
4.8%
Age | 60 to 64 years
Tragic
6.0%
Tragic
5.0%
Age | 65 to 74 years
Tragic
5.9%
Tragic
5.5%
Seniors > 65
Tragic
5.7%
Tragic
5.3%
Seniors > 75
Tragic
9.1%
Tragic
9.0%
Women w/ Children < 6
Tragic
8.8%
Good
7.5%
Women w/ Children 6 to 17
Good
8.8%
Tragic
9.2%
Women w/ Children < 18
Tragic
6.4%
Poor
5.6%

Immigrants from Bangladesh vs Peruvian Labor Participation

When considering labor participation, the most significant differences between Immigrants from Bangladesh and Peruvian communities in the United States are seen in in labor force | age 16-19 (30.0% compared to 34.6%, a difference of 15.1%), in labor force | age 20-24 (70.6% compared to 74.5%, a difference of 5.5%), and in labor force | age 45-54 (80.7% compared to 83.6%, a difference of 3.5%). Conversely, both communities are more comparable in terms of in labor force | age 30-34 (83.6% compared to 84.8%, a difference of 1.4%), in labor force | age 25-29 (83.0% compared to 84.7%, a difference of 2.1%), and in labor force | age 35-44 (82.9% compared to 84.9%, a difference of 2.4%).
Immigrants from Bangladesh vs Peruvian Labor Participation
Labor Participation MetricImmigrants from BangladeshPeruvian
In Labor Force | Age > 16
Tragic
64.5%
Exceptional
66.3%
In Labor Force | Age 20-64
Tragic
77.9%
Exceptional
80.3%
In Labor Force | Age 16-19
Tragic
30.0%
Tragic
34.6%
In Labor Force | Age 20-24
Tragic
70.6%
Poor
74.5%
In Labor Force | Age 25-29
Tragic
83.0%
Good
84.7%
In Labor Force | Age 30-34
Tragic
83.6%
Good
84.8%
In Labor Force | Age 35-44
Tragic
82.9%
Exceptional
84.9%
In Labor Force | Age 45-54
Tragic
80.7%
Exceptional
83.6%

Immigrants from Bangladesh vs Peruvian Family Structure

When considering family structure, the most significant differences between Immigrants from Bangladesh and Peruvian communities in the United States are seen in single father households (2.1% compared to 2.4%, a difference of 15.0%), married-couple households (43.1% compared to 47.6%, a difference of 10.5%), and divorced or separated (11.0% compared to 11.9%, a difference of 8.6%). Conversely, both communities are more comparable in terms of average family size (3.36 compared to 3.30, a difference of 1.9%), births to unmarried women (30.9% compared to 31.5%, a difference of 2.0%), and family households (63.9% compared to 67.1%, a difference of 5.1%).
Immigrants from Bangladesh vs Peruvian Family Structure
Family Structure MetricImmigrants from BangladeshPeruvian
Family Households
Poor
63.9%
Exceptional
67.1%
Family Households with Children
Good
27.6%
Exceptional
29.0%
Married-couple Households
Tragic
43.1%
Exceptional
47.6%
Average Family Size
Exceptional
3.36
Exceptional
3.30
Single Father Households
Exceptional
2.1%
Fair
2.4%
Single Mother Households
Tragic
6.9%
Fair
6.5%
Currently Married
Tragic
43.6%
Average
46.6%
Divorced or Separated
Exceptional
11.0%
Excellent
11.9%
Births to Unmarried Women
Good
30.9%
Average
31.5%

Immigrants from Bangladesh vs Peruvian Vehicle Availability

When considering vehicle availability, the most significant differences between Immigrants from Bangladesh and Peruvian communities in the United States are seen in no vehicles in household (25.8% compared to 11.2%, a difference of 129.0%), 4 or more vehicles in household (3.9% compared to 6.5%, a difference of 65.6%), and 3 or more vehicles in household (12.5% compared to 19.6%, a difference of 56.8%). Conversely, both communities are more comparable in terms of 1 or more vehicles in household (74.3% compared to 88.8%, a difference of 19.6%), 2 or more vehicles in household (38.8% compared to 55.0%, a difference of 41.8%), and 3 or more vehicles in household (12.5% compared to 19.6%, a difference of 56.8%).
Immigrants from Bangladesh vs Peruvian Vehicle Availability
Vehicle Availability MetricImmigrants from BangladeshPeruvian
No Vehicles Available
Tragic
25.8%
Tragic
11.2%
1+ Vehicles Available
Tragic
74.3%
Tragic
88.8%
2+ Vehicles Available
Tragic
38.8%
Fair
55.0%
3+ Vehicles Available
Tragic
12.5%
Average
19.6%
4+ Vehicles Available
Tragic
3.9%
Good
6.5%

Immigrants from Bangladesh vs Peruvian Education Level

When considering education level, the most significant differences between Immigrants from Bangladesh and Peruvian communities in the United States are seen in no schooling completed (3.1% compared to 2.4%, a difference of 31.7%), college, under 1 year (61.3% compared to 64.1%, a difference of 4.6%), and college, 1 year or more (56.6% compared to 58.6%, a difference of 3.7%). Conversely, both communities are more comparable in terms of nursery school (96.9% compared to 97.6%, a difference of 0.79%), kindergarten (96.8% compared to 97.6%, a difference of 0.80%), and 1st grade (96.8% compared to 97.6%, a difference of 0.81%).
Immigrants from Bangladesh vs Peruvian Education Level
Education Level MetricImmigrants from BangladeshPeruvian
No Schooling Completed
Tragic
3.1%
Tragic
2.4%
Nursery School
Tragic
96.9%
Tragic
97.6%
Kindergarten
Tragic
96.8%
Tragic
97.6%
1st Grade
Tragic
96.8%
Tragic
97.6%
2nd Grade
Tragic
96.7%
Tragic
97.5%
3rd Grade
Tragic
96.6%
Tragic
97.4%
4th Grade
Tragic
96.2%
Tragic
97.1%
5th Grade
Tragic
96.0%
Tragic
96.8%
6th Grade
Tragic
95.4%
Tragic
96.4%
7th Grade
Tragic
94.0%
Tragic
95.1%
8th Grade
Tragic
93.6%
Tragic
94.7%
9th Grade
Tragic
92.4%
Tragic
93.8%
10th Grade
Tragic
91.0%
Tragic
92.6%
11th Grade
Tragic
89.5%
Tragic
91.5%
12th Grade, No Diploma
Tragic
88.0%
Tragic
90.2%
High School Diploma
Tragic
85.5%
Tragic
87.8%
GED/Equivalency
Tragic
81.9%
Tragic
84.7%
College, Under 1 year
Tragic
61.3%
Poor
64.1%
College, 1 year or more
Tragic
56.6%
Fair
58.6%
Associate's Degree
Fair
45.2%
Average
46.4%
Bachelor's Degree
Average
37.8%
Good
38.3%
Master's Degree
Good
15.5%
Good
15.3%
Professional Degree
Average
4.4%
Good
4.5%
Doctorate Degree
Average
1.8%
Fair
1.8%

Immigrants from Bangladesh vs Peruvian Disability

When considering disability, the most significant differences between Immigrants from Bangladesh and Peruvian communities in the United States are seen in disability age under 5 (0.85% compared to 1.3%, a difference of 47.0%), hearing disability (2.4% compared to 2.7%, a difference of 12.6%), and disability age 35 to 64 (10.9% compared to 9.9%, a difference of 10.3%). Conversely, both communities are more comparable in terms of male disability (10.3% compared to 10.4%, a difference of 0.69%), disability (11.0% compared to 10.9%, a difference of 1.7%), and disability age over 75 (48.0% compared to 46.8%, a difference of 2.5%).
Immigrants from Bangladesh vs Peruvian Disability
Disability MetricImmigrants from BangladeshPeruvian
Disability
Exceptional
11.0%
Exceptional
10.9%
Males
Exceptional
10.3%
Exceptional
10.4%
Females
Exceptional
11.8%
Exceptional
11.3%
Age | Under 5 years
Exceptional
0.85%
Fair
1.3%
Age | 5 to 17 years
Exceptional
5.2%
Exceptional
5.3%
Age | 18 to 34 years
Exceptional
5.6%
Exceptional
6.0%
Age | 35 to 64 years
Excellent
10.9%
Exceptional
9.9%
Age | 65 to 74 years
Fair
23.6%
Exceptional
22.2%
Age | Over 75 years
Tragic
48.0%
Excellent
46.8%
Vision
Good
2.1%
Exceptional
2.1%
Hearing
Exceptional
2.4%
Exceptional
2.7%
Cognitive
Tragic
17.8%
Exceptional
16.7%
Ambulatory
Fair
6.2%
Exceptional
5.7%
Self-Care
Tragic
2.6%
Exceptional
2.4%