Lithuanian vs Malaysian 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)IndonesianInupiatIranianIraqiIrishIroquoisIsraeliItalianJamaicanJapaneseJordanianKenyanKiowaKoreanLaotianLatvianLebaneseLiberianLithuanianLumbeeLuxembourgerMacedonianMalteseMarshalleseMenomineeMexicanMexican 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
Malaysian
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

Malaysians

Excellent
Fair
8,827
SOCIAL INDEX
85.7/ 100
SOCIAL RATING
46th/ 347
SOCIAL RANK
3,136
SOCIAL INDEX
28.9/ 100
SOCIAL RATING
232nd/ 347
SOCIAL RANK

Malaysian Integration in Lithuanian Communities

The statistical analysis conducted on geographies consisting of 198,384,323 people shows a strong positive correlation between the proportion of Malaysians within Lithuanian communities in the United States with a correlation coefficient (R) of 0.773. On average, for every 1% (one percent) increase in Lithuanians within a typical geography, there is an increase of 0.219% in Malaysians. To illustrate, in a geography comprising of 100,000 individuals, a rise of 1,000 Lithuanians corresponds to an increase of 218.6 Malaysians.
Lithuanian Integration in Malaysian Communities

Lithuanian vs Malaysian Income

When considering income, the most significant differences between Lithuanian and Malaysian communities in the United States are seen in per capita income ($49,448 compared to $39,194, a difference of 26.2%), median family income ($115,395 compared to $95,230, a difference of 21.2%), and median male earnings ($61,228 compared to $50,772, a difference of 20.6%). Conversely, both communities are more comparable in terms of householder income under 25 years ($53,552 compared to $51,615, a difference of 3.7%), householder income over 65 years ($65,209 compared to $58,244, a difference of 12.0%), and median female earnings ($42,108 compared to $37,298, a difference of 12.9%).
Lithuanian vs Malaysian Income
Income MetricLithuanianMalaysian
Per Capita Income
Exceptional
$49,448
Tragic
$39,194
Median Family Income
Exceptional
$115,395
Tragic
$95,230
Median Household Income
Exceptional
$93,852
Tragic
$81,064
Median Earnings
Exceptional
$50,991
Tragic
$43,844
Median Male Earnings
Exceptional
$61,228
Tragic
$50,772
Median Female Earnings
Exceptional
$42,108
Tragic
$37,298
Householder Age | Under 25 years
Exceptional
$53,552
Poor
$51,615
Householder Age | 25 - 44 years
Exceptional
$105,223
Tragic
$88,291
Householder Age | 45 - 64 years
Exceptional
$112,484
Tragic
$94,517
Householder Age | Over 65 years
Exceptional
$65,209
Tragic
$58,244
Wage/Income Gap
Tragic
28.7%
Excellent
25.0%

Lithuanian vs Malaysian Poverty

When considering poverty, the most significant differences between Lithuanian and Malaysian communities in the United States are seen in married-couple family poverty (4.0% compared to 5.4%, a difference of 35.2%), family poverty (7.2% compared to 9.6%, a difference of 34.1%), and receiving food stamps (9.7% compared to 12.7%, a difference of 31.5%). Conversely, both communities are more comparable in terms of single male poverty (13.0% compared to 12.6%, a difference of 3.1%), female poverty among 18-24 year olds (18.7% compared to 19.9%, a difference of 6.2%), and single mother poverty (27.4% compared to 29.7%, a difference of 8.4%).
Lithuanian vs Malaysian Poverty
Poverty MetricLithuanianMalaysian
Poverty
Exceptional
10.5%
Tragic
13.1%
Families
Exceptional
7.2%
Poor
9.6%
Males
Exceptional
9.5%
Tragic
12.0%
Females
Exceptional
11.4%
Tragic
14.3%
Females 18 to 24 years
Exceptional
18.7%
Good
19.9%
Females 25 to 34 years
Exceptional
12.2%
Tragic
14.7%
Children Under 5 years
Exceptional
15.2%
Tragic
18.4%
Children Under 16 years
Exceptional
13.5%
Tragic
17.5%
Boys Under 16 years
Exceptional
14.0%
Tragic
17.6%
Girls Under 16 years
Exceptional
13.9%
Tragic
17.8%
Single Males
Fair
13.0%
Good
12.6%
Single Females
Exceptional
19.2%
Tragic
22.2%
Single Fathers
Tragic
17.3%
Exceptional
14.9%
Single Mothers
Exceptional
27.4%
Poor
29.7%
Married Couples
Exceptional
4.0%
Fair
5.4%
Seniors Over 65 years
Exceptional
9.1%
Good
10.8%
Seniors Over 75 years
Exceptional
10.6%
Excellent
11.8%
Receiving Food Stamps
Exceptional
9.7%
Tragic
12.7%

Lithuanian vs Malaysian Unemployment

When considering unemployment, the most significant differences between Lithuanian and Malaysian communities in the United States are seen in female unemployment (4.7% compared to 5.3%, a difference of 11.5%), unemployment among seniors over 75 years (9.9% compared to 8.9%, a difference of 10.6%), and unemployment among women with children ages 6 to 17 years (9.4% compared to 8.6%, a difference of 10.3%). Conversely, both communities are more comparable in terms of unemployment among women with children under 6 years (7.8% compared to 7.7%, a difference of 0.090%), unemployment among ages 25 to 29 years (6.5% compared to 6.6%, a difference of 0.38%), and unemployment among youth under 25 years (11.3% compared to 11.4%, a difference of 0.86%).
Lithuanian vs Malaysian Unemployment
Unemployment MetricLithuanianMalaysian
Unemployment
Exceptional
4.8%
Average
5.3%
Males
Exceptional
5.0%
Fair
5.3%
Females
Exceptional
4.7%
Average
5.3%
Youth < 25
Exceptional
11.3%
Excellent
11.4%
Age | 16 to 19 years
Exceptional
16.7%
Exceptional
17.0%
Age | 20 to 24 years
Good
10.2%
Exceptional
9.8%
Age | 25 to 29 years
Good
6.5%
Good
6.6%
Age | 30 to 34 years
Good
5.4%
Average
5.5%
Age | 35 to 44 years
Exceptional
4.4%
Fair
4.7%
Age | 45 to 54 years
Exceptional
4.3%
Average
4.5%
Age | 55 to 59 years
Excellent
4.7%
Exceptional
4.7%
Age | 60 to 64 years
Excellent
4.8%
Exceptional
4.7%
Age | 65 to 74 years
Fair
5.4%
Exceptional
5.2%
Seniors > 65
Average
5.1%
Exceptional
5.1%
Seniors > 75
Tragic
9.9%
Poor
8.9%
Women w/ Children < 6
Fair
7.8%
Fair
7.7%
Women w/ Children 6 to 17
Tragic
9.4%
Exceptional
8.6%
Women w/ Children < 18
Exceptional
5.0%
Fair
5.5%

Lithuanian vs Malaysian Labor Participation

When considering labor participation, the most significant differences between Lithuanian and Malaysian communities in the United States are seen in in labor force | age > 16 (64.8% compared to 66.1%, a difference of 2.0%), in labor force | age 45-54 (83.6% compared to 82.0%, a difference of 1.9%), and in labor force | age 16-19 (40.4% compared to 39.7%, a difference of 1.8%). Conversely, both communities are more comparable in terms of in labor force | age 20-24 (77.0% compared to 77.2%, a difference of 0.35%), in labor force | age 20-64 (80.2% compared to 79.5%, a difference of 0.97%), and in labor force | age 25-29 (85.8% compared to 84.6%, a difference of 1.4%).
Lithuanian vs Malaysian Labor Participation
Labor Participation MetricLithuanianMalaysian
In Labor Force | Age > 16
Poor
64.8%
Exceptional
66.1%
In Labor Force | Age 20-64
Exceptional
80.2%
Fair
79.5%
In Labor Force | Age 16-19
Exceptional
40.4%
Exceptional
39.7%
In Labor Force | Age 20-24
Exceptional
77.0%
Exceptional
77.2%
In Labor Force | Age 25-29
Exceptional
85.8%
Average
84.6%
In Labor Force | Age 30-34
Exceptional
85.6%
Tragic
84.1%
In Labor Force | Age 35-44
Exceptional
85.2%
Tragic
83.8%
In Labor Force | Age 45-54
Exceptional
83.6%
Tragic
82.0%

Lithuanian vs Malaysian Family Structure

When considering family structure, the most significant differences between Lithuanian and Malaysian communities in the United States are seen in single mother households (5.4% compared to 7.3%, a difference of 34.4%), single father households (2.1% compared to 2.7%, a difference of 29.3%), and births to unmarried women (29.6% compared to 33.9%, a difference of 14.6%). Conversely, both communities are more comparable in terms of family households (64.0% compared to 65.9%, a difference of 2.9%), divorced or separated (11.7% compared to 12.4%, a difference of 5.4%), and married-couple households (48.9% compared to 46.3%, a difference of 5.6%).
Lithuanian vs Malaysian Family Structure
Family Structure MetricLithuanianMalaysian
Family Households
Fair
64.0%
Exceptional
65.9%
Family Households with Children
Tragic
26.6%
Exceptional
29.8%
Married-couple Households
Exceptional
48.9%
Average
46.3%
Average Family Size
Tragic
3.10
Exceptional
3.31
Single Father Households
Exceptional
2.1%
Tragic
2.7%
Single Mother Households
Exceptional
5.4%
Tragic
7.3%
Currently Married
Exceptional
49.0%
Poor
45.9%
Divorced or Separated
Exceptional
11.7%
Tragic
12.4%
Births to Unmarried Women
Exceptional
29.6%
Tragic
33.9%

Lithuanian vs Malaysian Vehicle Availability

When considering vehicle availability, the most significant differences between Lithuanian and Malaysian communities in the United States are seen in 4 or more vehicles in household (6.3% compared to 7.7%, a difference of 21.1%), 3 or more vehicles in household (20.1% compared to 22.6%, a difference of 12.4%), and no vehicles in household (8.4% compared to 7.7%, a difference of 9.4%). Conversely, both communities are more comparable in terms of 1 or more vehicles in household (91.7% compared to 92.3%, a difference of 0.67%), 2 or more vehicles in household (58.2% compared to 59.8%, a difference of 2.8%), and no vehicles in household (8.4% compared to 7.7%, a difference of 9.4%).
Lithuanian vs Malaysian Vehicle Availability
Vehicle Availability MetricLithuanianMalaysian
No Vehicles Available
Exceptional
8.4%
Exceptional
7.7%
1+ Vehicles Available
Exceptional
91.7%
Exceptional
92.3%
2+ Vehicles Available
Exceptional
58.2%
Exceptional
59.8%
3+ Vehicles Available
Excellent
20.1%
Exceptional
22.6%
4+ Vehicles Available
Average
6.3%
Exceptional
7.7%

Lithuanian vs Malaysian Education Level

When considering education level, the most significant differences between Lithuanian and Malaysian communities in the United States are seen in no schooling completed (1.4% compared to 2.8%, a difference of 92.6%), professional degree (5.4% compared to 3.4%, a difference of 58.6%), and doctorate degree (2.3% compared to 1.5%, a difference of 55.1%). Conversely, both communities are more comparable in terms of nursery school (98.6% compared to 97.3%, a difference of 1.4%), kindergarten (98.6% compared to 97.2%, a difference of 1.4%), and 1st grade (98.6% compared to 97.2%, a difference of 1.4%).
Lithuanian vs Malaysian Education Level
Education Level MetricLithuanianMalaysian
No Schooling Completed
Exceptional
1.4%
Tragic
2.8%
Nursery School
Exceptional
98.6%
Tragic
97.3%
Kindergarten
Exceptional
98.6%
Tragic
97.2%
1st Grade
Exceptional
98.6%
Tragic
97.2%
2nd Grade
Exceptional
98.5%
Tragic
97.1%
3rd Grade
Exceptional
98.5%
Tragic
97.0%
4th Grade
Exceptional
98.3%
Tragic
96.7%
5th Grade
Exceptional
98.2%
Tragic
96.5%
6th Grade
Exceptional
98.1%
Tragic
96.2%
7th Grade
Exceptional
97.5%
Tragic
94.8%
8th Grade
Exceptional
97.3%
Tragic
94.5%
9th Grade
Exceptional
96.6%
Tragic
93.5%
10th Grade
Exceptional
95.8%
Tragic
92.2%
11th Grade
Exceptional
94.8%
Tragic
90.8%
12th Grade, No Diploma
Exceptional
93.6%
Tragic
89.2%
High School Diploma
Exceptional
92.0%
Tragic
87.0%
GED/Equivalency
Exceptional
88.9%
Tragic
83.3%
College, Under 1 year
Exceptional
68.8%
Tragic
62.2%
College, 1 year or more
Exceptional
62.9%
Tragic
55.6%
Associate's Degree
Exceptional
50.6%
Tragic
41.6%
Bachelor's Degree
Exceptional
42.2%
Tragic
32.9%
Master's Degree
Exceptional
17.7%
Tragic
12.0%
Professional Degree
Exceptional
5.4%
Tragic
3.4%
Doctorate Degree
Exceptional
2.3%
Tragic
1.5%

Lithuanian vs Malaysian Disability

When considering disability, the most significant differences between Lithuanian and Malaysian communities in the United States are seen in disability age under 5 (1.6% compared to 1.3%, a difference of 20.7%), disability age 65 to 74 (21.4% compared to 25.4%, a difference of 18.8%), and disability age 35 to 64 (10.8% compared to 12.5%, a difference of 15.5%). Conversely, both communities are more comparable in terms of disability age 5 to 17 (5.8% compared to 5.8%, a difference of 0.86%), male disability (11.6% compared to 11.8%, a difference of 1.8%), and disability (11.9% compared to 12.2%, a difference of 2.4%).
Lithuanian vs Malaysian Disability
Disability MetricLithuanianMalaysian
Disability
Poor
11.9%
Tragic
12.2%
Males
Tragic
11.6%
Tragic
11.8%
Females
Average
12.2%
Tragic
12.5%
Age | Under 5 years
Tragic
1.6%
Poor
1.3%
Age | 5 to 17 years
Tragic
5.8%
Tragic
5.8%
Age | 18 to 34 years
Tragic
7.0%
Tragic
7.2%
Age | 35 to 64 years
Excellent
10.8%
Tragic
12.5%
Age | 65 to 74 years
Exceptional
21.4%
Tragic
25.4%
Age | Over 75 years
Exceptional
45.1%
Tragic
49.0%
Vision
Exceptional
2.0%
Tragic
2.3%
Hearing
Tragic
3.4%
Tragic
3.2%
Cognitive
Exceptional
16.3%
Tragic
17.9%
Ambulatory
Excellent
6.0%
Fair
6.2%
Self-Care
Exceptional
2.4%
Tragic
2.5%