Japanese vs Lithuanian Community Comparison

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Japanese
Race
Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican 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
Lithuanian
Race
Ancestry
AfghanAfricanAlaska NativeAlaskan AthabascanAlbanianAleutAlsatianAmericanApacheArabArapahoArgentineanArmenianAssyrian/Chaldean/SyriacAustralianAustrianBahamianBangladeshiBarbadianBasqueBelgianBelizeanBermudanBhutaneseBlackfeetBolivianBrazilianBritishBritish West IndianBulgarianBurmeseCajunCambodianCanadianCape VerdeanCarpatho RusynCelticCentral AmericanCentral American IndianCherokeeCheyenneChickasawChileanChineseChippewaChoctawColombianColvilleComancheCosta RicanCreeCreekCroatianCrowCubanCypriotCzechCzechoslovakianDanishDelawareDominicanDutchDutch West IndianEastern EuropeanEcuadorianEgyptianEnglishEstonianEthiopianEuropeanFijianFilipinoFinnishFrenchFrench American IndianFrench CanadianGermanGerman RussianGhanaianGreekGuamanian/ChamorroGuatemalanGuyaneseHaitianHmongHonduranHopiHoumaHungarianIcelanderIndian (Asian)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalaysianMalteseMarshalleseMenomineeMexicanMexican 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

Japanese

Lithuanians

Fair
Excellent
2,662
SOCIAL INDEX
24.2/ 100
SOCIAL RATING
248th/ 347
SOCIAL RANK
8,827
SOCIAL INDEX
85.7/ 100
SOCIAL RATING
46th/ 347
SOCIAL RANK

Lithuanian Integration in Japanese Communities

The statistical analysis conducted on geographies consisting of 220,087,000 people shows no correlation between the proportion of Lithuanians within Japanese communities in the United States with a correlation coefficient (R) of -0.024. On average, for every 1% (one percent) increase in Japanese within a typical geography, there is a decrease of 0.001% in Lithuanians. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Japanese corresponds to a decrease of 0.7 Lithuanians.
Japanese Integration in Lithuanian Communities

Japanese vs Lithuanian Income

When considering income, the most significant differences between Japanese and Lithuanian communities in the United States are seen in per capita income ($39,870 compared to $49,448, a difference of 24.0%), wage/income gap (23.8% compared to 28.7%, a difference of 20.8%), and median male earnings ($51,473 compared to $61,228, a difference of 19.0%). Conversely, both communities are more comparable in terms of householder income under 25 years ($52,365 compared to $53,552, a difference of 2.3%), median female earnings ($38,528 compared to $42,108, a difference of 9.3%), and median household income ($83,395 compared to $93,852, a difference of 12.5%).
Japanese vs Lithuanian Income
Income MetricJapaneseLithuanian
Per Capita Income
Tragic
$39,870
Exceptional
$49,448
Median Family Income
Tragic
$97,288
Exceptional
$115,395
Median Household Income
Fair
$83,395
Exceptional
$93,852
Median Earnings
Tragic
$44,825
Exceptional
$50,991
Median Male Earnings
Tragic
$51,473
Exceptional
$61,228
Median Female Earnings
Tragic
$38,528
Exceptional
$42,108
Householder Age | Under 25 years
Good
$52,365
Exceptional
$53,552
Householder Age | 25 - 44 years
Poor
$91,624
Exceptional
$105,223
Householder Age | 45 - 64 years
Poor
$96,834
Exceptional
$112,484
Householder Age | Over 65 years
Tragic
$57,919
Exceptional
$65,209
Wage/Income Gap
Exceptional
23.8%
Tragic
28.7%

Japanese vs Lithuanian Poverty

When considering poverty, the most significant differences between Japanese and Lithuanian communities in the United States are seen in receiving food stamps (14.1% compared to 9.7%, a difference of 45.8%), married-couple family poverty (5.6% compared to 4.0%, a difference of 40.3%), and family poverty (9.9% compared to 7.2%, a difference of 37.6%). Conversely, both communities are more comparable in terms of single male poverty (13.1% compared to 13.0%, a difference of 0.63%), female poverty among 18-24 year olds (18.8% compared to 18.7%, a difference of 0.67%), and single mother poverty (28.9% compared to 27.4%, a difference of 5.5%).
Japanese vs Lithuanian Poverty
Poverty MetricJapaneseLithuanian
Poverty
Tragic
13.3%
Exceptional
10.5%
Families
Tragic
9.9%
Exceptional
7.2%
Males
Tragic
12.2%
Exceptional
9.5%
Females
Tragic
14.5%
Exceptional
11.4%
Females 18 to 24 years
Exceptional
18.8%
Exceptional
18.7%
Females 25 to 34 years
Poor
14.1%
Exceptional
12.2%
Children Under 5 years
Poor
18.1%
Exceptional
15.2%
Children Under 16 years
Tragic
17.7%
Exceptional
13.5%
Boys Under 16 years
Tragic
17.7%
Exceptional
14.0%
Girls Under 16 years
Tragic
17.8%
Exceptional
13.9%
Single Males
Poor
13.1%
Fair
13.0%
Single Females
Fair
21.3%
Exceptional
19.2%
Single Fathers
Exceptional
15.2%
Tragic
17.3%
Single Mothers
Good
28.9%
Exceptional
27.4%
Married Couples
Tragic
5.6%
Exceptional
4.0%
Seniors Over 65 years
Tragic
12.2%
Exceptional
9.1%
Seniors Over 75 years
Tragic
13.3%
Exceptional
10.6%
Receiving Food Stamps
Tragic
14.1%
Exceptional
9.7%

Japanese vs Lithuanian Unemployment

When considering unemployment, the most significant differences between Japanese and Lithuanian communities in the United States are seen in unemployment among seniors over 75 years (8.3% compared to 9.9%, a difference of 18.8%), female unemployment (5.6% compared to 4.7%, a difference of 18.2%), and unemployment (5.6% compared to 4.8%, a difference of 17.7%). Conversely, both communities are more comparable in terms of unemployment among ages 55 to 59 years (4.8% compared to 4.7%, a difference of 2.0%), unemployment among ages 20 to 24 years (10.0% compared to 10.2%, a difference of 2.1%), and unemployment among ages 65 to 74 years (5.2% compared to 5.4%, a difference of 3.4%).
Japanese vs Lithuanian Unemployment
Unemployment MetricJapaneseLithuanian
Unemployment
Tragic
5.6%
Exceptional
4.8%
Males
Tragic
5.8%
Exceptional
5.0%
Females
Tragic
5.6%
Exceptional
4.7%
Youth < 25
Fair
11.7%
Exceptional
11.3%
Age | 16 to 19 years
Average
17.6%
Exceptional
16.7%
Age | 20 to 24 years
Exceptional
10.0%
Good
10.2%
Age | 25 to 29 years
Tragic
6.9%
Good
6.5%
Age | 30 to 34 years
Tragic
5.9%
Good
5.4%
Age | 35 to 44 years
Tragic
5.1%
Exceptional
4.4%
Age | 45 to 54 years
Tragic
4.7%
Exceptional
4.3%
Age | 55 to 59 years
Average
4.8%
Excellent
4.7%
Age | 60 to 64 years
Tragic
5.1%
Excellent
4.8%
Age | 65 to 74 years
Exceptional
5.2%
Fair
5.4%
Seniors > 65
Exceptional
4.9%
Average
5.1%
Seniors > 75
Exceptional
8.3%
Tragic
9.9%
Women w/ Children < 6
Good
7.5%
Fair
7.8%
Women w/ Children 6 to 17
Exceptional
8.4%
Tragic
9.4%
Women w/ Children < 18
Tragic
5.7%
Exceptional
5.0%

Japanese vs Lithuanian Labor Participation

When considering labor participation, the most significant differences between Japanese and Lithuanian communities in the United States are seen in in labor force | age 16-19 (37.5% compared to 40.4%, a difference of 7.7%), in labor force | age 45-54 (81.6% compared to 83.6%, a difference of 2.5%), and in labor force | age 20-24 (75.3% compared to 77.0%, a difference of 2.2%). Conversely, both communities are more comparable in terms of in labor force | age 30-34 (84.3% compared to 85.6%, a difference of 1.5%), in labor force | age > 16 (65.8% compared to 64.8%, a difference of 1.5%), and in labor force | age 20-64 (79.1% compared to 80.2%, a difference of 1.5%).
Japanese vs Lithuanian Labor Participation
Labor Participation MetricJapaneseLithuanian
In Labor Force | Age > 16
Exceptional
65.8%
Poor
64.8%
In Labor Force | Age 20-64
Tragic
79.1%
Exceptional
80.2%
In Labor Force | Age 16-19
Excellent
37.5%
Exceptional
40.4%
In Labor Force | Age 20-24
Good
75.3%
Exceptional
77.0%
In Labor Force | Age 25-29
Poor
84.3%
Exceptional
85.8%
In Labor Force | Age 30-34
Tragic
84.3%
Exceptional
85.6%
In Labor Force | Age 35-44
Tragic
83.6%
Exceptional
85.2%
In Labor Force | Age 45-54
Tragic
81.6%
Exceptional
83.6%

Japanese vs Lithuanian Family Structure

When considering family structure, the most significant differences between Japanese and Lithuanian communities in the United States are seen in single mother households (7.4% compared to 5.4%, a difference of 36.2%), single father households (2.8% compared to 2.1%, a difference of 30.4%), and births to unmarried women (35.2% compared to 29.6%, a difference of 19.0%). Conversely, both communities are more comparable in terms of divorced or separated (12.0% compared to 11.7%, a difference of 2.0%), family households (65.9% compared to 64.0%, a difference of 2.9%), and average family size (3.35 compared to 3.10, a difference of 7.9%).
Japanese vs Lithuanian Family Structure
Family Structure MetricJapaneseLithuanian
Family Households
Exceptional
65.9%
Fair
64.0%
Family Households with Children
Exceptional
29.4%
Tragic
26.6%
Married-couple Households
Tragic
45.2%
Exceptional
48.9%
Average Family Size
Exceptional
3.35
Tragic
3.10
Single Father Households
Tragic
2.8%
Exceptional
2.1%
Single Mother Households
Tragic
7.4%
Exceptional
5.4%
Currently Married
Tragic
44.5%
Exceptional
49.0%
Divorced or Separated
Good
12.0%
Exceptional
11.7%
Births to Unmarried Women
Tragic
35.2%
Exceptional
29.6%

Japanese vs Lithuanian Vehicle Availability

When considering vehicle availability, the most significant differences between Japanese and Lithuanian communities in the United States are seen in 4 or more vehicles in household (7.7% compared to 6.3%, a difference of 21.6%), no vehicles in household (9.4% compared to 8.4%, a difference of 11.8%), and 3 or more vehicles in household (21.8% compared to 20.1%, a difference of 8.2%). Conversely, both communities are more comparable in terms of 1 or more vehicles in household (90.6% compared to 91.7%, a difference of 1.2%), 2 or more vehicles in household (57.5% compared to 58.2%, a difference of 1.3%), and 3 or more vehicles in household (21.8% compared to 20.1%, a difference of 8.2%).
Japanese vs Lithuanian Vehicle Availability
Vehicle Availability MetricJapaneseLithuanian
No Vehicles Available
Exceptional
9.4%
Exceptional
8.4%
1+ Vehicles Available
Exceptional
90.6%
Exceptional
91.7%
2+ Vehicles Available
Exceptional
57.5%
Exceptional
58.2%
3+ Vehicles Available
Exceptional
21.8%
Excellent
20.1%
4+ Vehicles Available
Exceptional
7.7%
Average
6.3%

Japanese vs Lithuanian Education Level

When considering education level, the most significant differences between Japanese and Lithuanian communities in the United States are seen in no schooling completed (3.3% compared to 1.4%, a difference of 132.9%), professional degree (3.5% compared to 5.4%, a difference of 51.7%), and doctorate degree (1.5% compared to 2.3%, a difference of 48.7%). Conversely, both communities are more comparable in terms of nursery school (96.7% compared to 98.6%, a difference of 2.0%), kindergarten (96.7% compared to 98.6%, a difference of 2.0%), and 1st grade (96.6% compared to 98.6%, a difference of 2.0%).
Japanese vs Lithuanian Education Level
Education Level MetricJapaneseLithuanian
No Schooling Completed
Tragic
3.3%
Exceptional
1.4%
Nursery School
Tragic
96.7%
Exceptional
98.6%
Kindergarten
Tragic
96.7%
Exceptional
98.6%
1st Grade
Tragic
96.6%
Exceptional
98.6%
2nd Grade
Tragic
96.5%
Exceptional
98.5%
3rd Grade
Tragic
96.4%
Exceptional
98.5%
4th Grade
Tragic
96.0%
Exceptional
98.3%
5th Grade
Tragic
95.7%
Exceptional
98.2%
6th Grade
Tragic
95.4%
Exceptional
98.1%
7th Grade
Tragic
94.0%
Exceptional
97.5%
8th Grade
Tragic
93.6%
Exceptional
97.3%
9th Grade
Tragic
92.6%
Exceptional
96.6%
10th Grade
Tragic
91.2%
Exceptional
95.8%
11th Grade
Tragic
89.9%
Exceptional
94.8%
12th Grade, No Diploma
Tragic
88.3%
Exceptional
93.6%
High School Diploma
Tragic
85.9%
Exceptional
92.0%
GED/Equivalency
Tragic
82.4%
Exceptional
88.9%
College, Under 1 year
Tragic
61.5%
Exceptional
68.8%
College, 1 year or more
Tragic
55.2%
Exceptional
62.9%
Associate's Degree
Tragic
41.7%
Exceptional
50.6%
Bachelor's Degree
Tragic
33.3%
Exceptional
42.2%
Master's Degree
Tragic
12.5%
Exceptional
17.7%
Professional Degree
Tragic
3.5%
Exceptional
5.4%
Doctorate Degree
Tragic
1.5%
Exceptional
2.3%

Japanese vs Lithuanian Disability

When considering disability, the most significant differences between Japanese and Lithuanian communities in the United States are seen in disability age under 5 (1.2% compared to 1.6%, a difference of 32.6%), disability age 65 to 74 (25.7% compared to 21.4%, a difference of 20.3%), and vision disability (2.4% compared to 2.0%, a difference of 15.8%). Conversely, both communities are more comparable in terms of male disability (11.7% compared to 11.6%, a difference of 1.1%), disability age 18 to 34 (6.8% compared to 7.0%, a difference of 2.1%), and disability (12.2% compared to 11.9%, a difference of 2.5%).
Japanese vs Lithuanian Disability
Disability MetricJapaneseLithuanian
Disability
Tragic
12.2%
Poor
11.9%
Males
Tragic
11.7%
Tragic
11.6%
Females
Tragic
12.6%
Average
12.2%
Age | Under 5 years
Exceptional
1.2%
Tragic
1.6%
Age | 5 to 17 years
Tragic
6.1%
Tragic
5.8%
Age | 18 to 34 years
Poor
6.8%
Tragic
7.0%
Age | 35 to 64 years
Tragic
12.3%
Excellent
10.8%
Age | 65 to 74 years
Tragic
25.7%
Exceptional
21.4%
Age | Over 75 years
Tragic
50.2%
Exceptional
45.1%
Vision
Tragic
2.4%
Exceptional
2.0%
Hearing
Average
3.0%
Tragic
3.4%
Cognitive
Tragic
18.3%
Exceptional
16.3%
Ambulatory
Poor
6.3%
Excellent
6.0%
Self-Care
Tragic
2.7%
Exceptional
2.4%