Demographics details for Long beach, WA vs Gilbert, AZ
Population Overview
Compare main population characteristics in Long beach, WA vs Gilbert, AZ.
| Data | Long beach | Gilbert |
|---|---|---|
| Population | 1,754 | 275,346 |
| Median Age | 51.3 years | 35.4 years |
| Median Income | $47,188 | $115,179 |
| Married Families | 41.0% | 42.0% |
| Poverty Level | 10% | 6% |
| Unemployment Rate | 5.5 | 3.0 |
Population Comparison: Long beach vs Gilbert
- The population in Gilbert is higher at 275,346, compared to 1,754 in Long beach.
- Residents in Long beach have a higher median age of 51.3 years compared to 35.4 years in Gilbert.
- Gilbert has a higher median income of $115,179, compared to $47,188 in Long beach.
- In Gilbert, the percentage of married families is higher at 42.0%, compared to 41.0% in Long beach.
- Long beach has a higher poverty level at 10% compared to 6% in Gilbert.
- The unemployment rate in Long beach is higher at 5.5%, compared to 3.0% in Gilbert.
Demographics
Demographics Long beach vs Gilbert provide insight into the diversity of the communities to compare.
| Demographic | Long beach | Gilbert |
|---|---|---|
| Black | Data is updating | 4 |
| White | 86 | 62 |
| Asian | 1 | 6 |
| Hispanic | 7 | 17 |
| Two or More Races | 5 | 10 |
| American Indian | 1 | 1 |
Demographics Comparison: Long beach vs Gilbert
- In Gilbert, the percentage of Black residents is higher at 4% compared to 0% in Long beach.
- Long beach has a higher percentage of White residents at 86% compared to 62% in Gilbert.
- In Gilbert, the Asian population stands at 6%, greater than 1% in Long beach.
- Gilbert has a higher percentage of Hispanic residents at 17%, compared to 7% in Long beach.
- The percentage of residents identifying as two or more races is higher in Gilbert at 10%, compared to 5% in Long beach.
- The percentage of American Indian residents is the same in both Long beach and Gilbert at 1%.
Health Statistics
The health statistics provide insights into prevalent health conditions in two communities.
| Health Metric | Long beach | Gilbert |
|---|---|---|
| Mental Health Not Good | 20.3% | 15.2% |
| Physical Health Not Good | 14.8% | 8.4% |
| Depression | 28.9% | 19.0% |
| Smoking | 20.1% | 11.3% |
| Binge Drinking | 16.2% | 19.1% |
| Obesity | 38.5% | 27.2% |
| Disability Percentage | 28.0% | 7.0% |
Health Statistics Comparison: Long beach vs Gilbert
- More residents in Long beach report poor mental health at 20.3% compared to 15.2% in Gilbert.
- Depression is more prevalent in Long beach at 28.9% compared to 19.0% in Gilbert.
- Smoking is more prevalent in Long beach at 20.1% compared to 11.3% in Gilbert.
- More residents engage in binge drinking in Gilbert at 19.1% compared to 16.2% in Long beach.
- Obesity rates are higher in Long beach at 38.5% compared to 27.2% in Gilbert.
- Disability percentages are higher in Long beach at 28.0% compared to 7.0% in Gilbert.
Education Levels
The educational attainment in the area helps gauge the workforce's skill level and economic potential.
| Education Level | Long beach | Gilbert |
|---|---|---|
| No Schooling | 0.0% (Data is updating) | 0.5% (1,279) |
| High School Diploma | 19.6% (343) | 8.1% (22,388) |
| Less than High School | 13.6% (238) | 4.0% (10,945) |
| Bachelor's Degree and Higher | 14.3% (250) | 28.4% (78,297) |
Education Levels Comparison: Long beach vs Gilbert
- In Gilbert, a larger percentage of residents lack formal schooling at 0.5% compared to 0.0% in Long beach.
- A higher percentage of residents in Long beach hold a high school diploma at 19.6% compared to 8.1% in Gilbert.
- More residents in Long beach have less than a high school education at 13.6% compared to 4.0% in Gilbert.
- In Gilbert, a larger share of residents have a bachelor's degree or higher at 28.4% compared to 14.3% in Long beach.
Crime and Safety
Understanding crime rates and safety measures is crucial for assessing the livability of a city or town. Crime levels can vary significantly from one neighborhood to another, influenced by various factors such as population density and local amenities. For instance, areas with high foot traffic, like train stations, might experience different crime dynamics compared to quieter residential neighborhoods. Evaluating these patterns helps in making informed decisions about safety and community well-being.