Zip Codes with the Fewest Births per 1,000 Women Over the Age of 35 in Germantown, MD

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Lowest Birth Rate | Women 35+

Population

Highest Population Highest Population Density Lowest Population Density Male / Female Ratio Female / Male Ratio Oldest Population Oldest Population | Male Oldest Population | Female Youngest Population Youngest Population | Male Youngest Population | Female

Families and Households

Largest Family Size Largest Household Size Most Single Fathers Most Single Mothers Fewest Single Fathers Fewest Single Mothers Smallest Family Size Smallest Household Size

Female Fertility

Female Fertility (Unmarried)

Highest Illegitimacy | All Women Highest Illegitimacy | Women 35+Lowest Illegitimacy | All Women Lowest Illegitimacy | Women 35+

Race (Community Size)

Asian Black / African American Hispanic or Latino Native / Alaskan White / Caucasian

Race (Percentage)

Asian Black / African American Hispanic or Latino Native / Alaskan White / Caucasian

Ancestry (Community Size)

African Albanian American Arab Argentinean Armenian Austrian Bhutanese Bolivian Brazilian British British West Indian Burmese Central American Central American Indian Cherokee Chilean Colombian Cuban Czech Danish Dominican Dutch Eastern European Ecuadorian Egyptian English Ethiopian European Filipino French French Canadian German Ghanaian Greek Guatemalan Guyanese Haitian Honduran Hungarian Indian (Asian)Indonesian Iranian Iraqi Irish Israeli Italian Jamaican Japanese Kenyan Korean Lebanese Lithuanian Mexican Nicaraguan Nigerian Northern European Norwegian Pakistani Panamanian Pennsylvania German Peruvian Polish Portuguese Puerto Rican Romanian Russian Salvadoran Scotch-Irish Scottish Serbian Sierra Leonean Slovak South American South American Indian Spaniard Sri Lankan Subsaharan African Swedish Swiss Syrian Thai Trinidadian and Tobagonian Turkish Ukrainian Welsh West Indian

Ancestry (Percentage)

Immigrant Origin (Total)

Africa Argentina Asia Bangladesh Bolivia Brazil Burma / Myanmar Cambodia Cameroon Canada Caribbean Central America Chile China Colombia Cuba Czechoslovakia Dominican Republic Eastern Africa Eastern Asia Eastern Europe Ecuador El Salvador Eritrea Ethiopia Europe Germany Ghana Guatemala Guyana Haiti Honduras Hong Kong India Iran Iraq Italy Jamaica Kenya Korea Laos Latin America Liberia Malaysia Mexico Middle Africa Nepal Netherlands Nicaragua Nigeria Northern Africa Northern Europe Oceania Pakistan Panama Peru Philippines Poland Russia Senegal Sierra Leone South America South Central Asia South Eastern Asia Southern Europe Sri Lanka Syria Taiwan Thailand Trinidad and Tobago Uzbekistan Vietnam Western Africa Western Asia Western Europe Zaire

Immigrant Origin (Percentage)

Income

Highest Per Capita Income Highest Earnings | Male Highest Earnings | Female Highest Wage/Income Gap ($)Highest Wage/Income Gap (%)Highest Inequality / Gini Index Lowest Per Capita Income Lowest Earnings | Male Lowest Earnings | Female Lowest Wage/Income Gap ($)Lowest Wage/Income Gap (%)Lowest Inequality / Gini Index

Income (Families)

Highest Family Income Lowest Family Income Family Income | $0-10k Family Income | $100k+Family Income | $200k+

Income (Households)

Highest Household Income Lowest Household Income Household Income | $0-10k Household Income | $200k+Household Income | $100k+

Poverty

Poverty (Families)

Unemployment

Employment Occupations

Architecture & Engineering Arts, Media & Entertainment Business & Financial Cleaning & Maintenance Community & Social Service Computer & Mathematics Computer, Engineering & Science Construction & Extraction Education Instruction & Library Education, Arts & Media Firefighting & Prevention Food Preparation & Serving Health Diagnosing & Treating Health Technologists Healthcare Support Installation, Maintenance & Repair Law Enforcement Legal Services & Support Life, Physical & Social Science Management Material Moving Office & Administration Personal Care and Service Production Sales & Related Security & Protection Transportation

Employment Industries

Accommodation & Food Services Administrative & Support Services Agriculture, Fishing & Hunting Arts, Entertainment & Recreation Construction Educational Services Enterprise Management Finance & Insurance Health Care & Social Assistance Information & Technology Manufacturing Professional & Scientific Services Public Administration Real Estate, Rental & Leasing Retail Trade Transportation & Warehousing Utilities Wholesale Trade

Employer Class

Private Company Employees Self-Employed / Incorporated Self-Employed / Not Incorporated Not-for-profit Organizations Local Government Employees State Government Employees Federal Government Employees Unpaid Family Workers

Commute Time

Longest Commute Longest Commute | Male Longest Commute | Female Shortest Commute Shortest Commute | Male Shortest Commute | Female

Commute Means

Drive | Alone Drive | Carpool Public Transit Taxi / Cab Walk to Work Work from Home

School Enrollment

In Private School Nursery / Preschool Kindergarten Elementary School Middle School High School College University

Education by Degree Field

Computers and Mathematics Bio, Nature & Agricultural Physical and Health Sciences Psychology Social Sciences Engineering Multidisciplinary Studies Science and Engineering Business Education Literature and Languages Liberal Arts and History Visual and Performing Arts Communications Arts and Humanities

Occupancy

Highest Owner-Occupied Highest Renter-Occupied Lowest Owner-Occupied Lowest Renter-Occupied

Finances

Highest Median Housing Costs Highest Property Prices Highest Owner Housing Costs Highest Renter Housing Costs Highest Housing Costs / Income Lowest Median Housing Costs Lowest Property Prices Lowest Owner Housing Costs Lowest Renter Housing Costs Lowest Housing Costs / Income

Physical Characteristics

Detached Home Residency Condo/Apartment Residency Utility Gas Heating Bottled Gas / LP Heating Electrical Heating Fuel Oil Heating Fuel-less Heating Households without a Cars Households with 1 or more Cars Households with 2 or more Cars Households with 3 or more Cars

Germantown

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Map of Zip Codes with the Fewest Births per 1,000 Women Over the Age of 35 in Germantown

40.0

0.0

Zip Codes with the Fewest Births per 1,000 Women Over the Age of 35 in Germantown Map

Zip Codes with the Fewest Births per 1,000 Women Over the Age of 35 in Germantown, MD

	Zip Code	Births / 1,000 Women	vs State	vs National
1.	20874	32.0	38.0(-6.00)#105	32.0(=0.000)#8,147
2.	20876	38.0	38.0(=0.000)#138	32.0(+6.00)#9,790

Common Questions

What are the Top Zip Codes with the Fewest Births per 1,000 Women Over the Age of 35 in Germantown, MD?

Top Zip Codes with the Fewest Births per 1,000 Women Over the Age of 35 in Germantown, MD are:

20874

32.0

20876

38.0

What zip code has the Fewest Births per 1,000 Women Over the Age of 35 in Germantown, MD?

20874 has the Fewest Births per 1,000 Women Over the Age of 35 in Germantown, MD with 32.0.

What is the Number of Births per 1,000 Women Over the Age of 35 in Germantown, MD?

Number of Births per 1,000 Women Over the Age of 35 in Germantown is 36.0.

What is the Number of Births per 1,000 Women Over the Age of 35 in Maryland?

Number of Births per 1,000 Women Over the Age of 35 in Maryland is 38.0.

What is the Number of Births per 1,000 Women Over the Age of 35 in the United States?

Number of Births per 1,000 Women Over the Age of 35 in the United States is 32.0.