Lithuanian vs Japanese Community Comparison

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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
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
Social Comparison
Social Comparison
Income
Poverty
Unemployment
Labor Participation
Family Structure
Vehicle Availability
Education Level
Disability

Social Comparison

Lithuanians

Japanese

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

Japanese Integration in Lithuanian Communities

The statistical analysis conducted on geographies consisting of 220,087,000 people shows a very strong positive correlation between the proportion of Japanese within Lithuanian communities in the United States with a correlation coefficient (R) of 0.871. On average, for every 1% (one percent) increase in Lithuanians within a typical geography, there is an increase of 0.251% in Japanese. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Lithuanians corresponds to an increase of 250.9 Japanese.
Lithuanian Integration in Japanese Communities

Lithuanian vs Japanese Income

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

Lithuanian vs Japanese Poverty

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

Lithuanian vs Japanese Unemployment

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

Lithuanian vs Japanese Labor Participation

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

Lithuanian vs Japanese Family Structure

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

Lithuanian vs Japanese Vehicle Availability

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

Lithuanian vs Japanese Education Level

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

Lithuanian vs Japanese Disability

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