Health Determinants

The Healthy NC 2030 taskforce, led by the North Carolina Institute of Medicine and the North Carolina Department of Health and Human Services, brought together experts and leaders from various fields to develop a common set of public health indicators and targets for the state over the next decade. The full report, published in January 2020, established a north star for city, county, and state governments, as well as local organizations to mobilize to accomplish North Carolina’s most pressing housing, education, public health, and economic opportunity goals.

Health is largely determined by social, economic, behavioral, and environmental factors, all of which affect health outcomes. These factors, known as social determinants of health, include safe housing, racism, literacy skills, and job opportunities. Social determinants of health serve as a gauge for wellness and quality of life.

In 2022, Cape Fear Collective, a regional nonprofit, took Healthy NC 2030’s data and launched the Healthy Communities Dashboard. This free, publicly available data analysis tool can be used by community members and nonprofits to take a deeper dive into community data related to the health indicators that are most relevant to our region.

Cape Fear Collective’s Director of Data Science Nicholas Pylypiw says the dashboard was created after talking to Novant Health New Hanover Regional Medical Center, UNC Wilmington, and other organizations about what metrics are important. “More than 1,300 metrics were found to be important. So, we anchored their data with the 21 indicators that mirror those in the Healthy NC 2030 report,” he says. “There’s no shortage of passion in support of nonprofits, but some are lacking the data or analysis to establish a marker when creating plans to make change.”

The Healthy Communities Dashboard helps them generate hypotheses, set goals, measure programs, and have understandable and digestible data to support their work – and for grant applications. “The data also shows common goals, so multiple organizations who are doing similar work can work together to improve health outcomes,” Pylypiw adds.

Cape Fear Collective is also working to figure out how data is interconnected. For example, would improving poverty increase life expectancy? Pylypiw indicates there were not a lot of surprises in the data. “I am surprised by the magnitude of the difference,” he says. Here are some specific statistics related to women’s health in New Hanover County:

• Infant Mortality: In the last ten years, New Hanover County has dropped several places regarding infant mortality – from one of the lowest in the state (98th) to now just 74th. Currently, New Hanover County has an infant mortality rate of 6.7 infant deaths per 1,000 live births (up from 4.2 in 2015). For Black mothers in the county, this number rises to 11.1 (4.3 for White mothers).
• Prenatal Care: New Hanover County is in the bottom quartile of the state (79th) with only 63.9% of women receiving pregnancy-related health care services during the first trimester of a pregnancy. While 68.9% of White non-Hispanic women in the county receive this care, the number drops significantly for Black and Hispanic women (53.7% and 49.6%, respectively). All three of these groups have seen double digit decreases since 2013 and are well below the 80% goal set by NCDHHS and NCIOM.
• Teen Birth: New Hanover County has one of the lowest teen birth rates in the state (86th), with only .87 (per 1,000 live births). However, the racial and ethnic disparity is significant. The teen birth rate for Black (3.09) and Hispanic (3.49) mothers is five times that of White mothers (.68).
• Unemployment: Over the last 12 years, women have had a lower unemployment rate than men in New Hanover County. However, that trend has shifted over the past few years.
• Poverty: In New Hanover County, 17.7% of women are currently below the Federal Poverty Line (compared to 14.2% of men). This disparity is present in almost every age bracket, but is most pronounced in the 75+ group, where the rate of women in poverty is double that of their male peers (11.9% vs. 5.9%).

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