2281-PUB: Family Impact Module in NYC: Diabetes vs. Community Sample

Introduction: We previously reported parents of a child with diabetes (CWD) score poorly on the Pediatric Quality of Life (QoL) Family Impact Module (FIM). Use of the FIM in parents of a CWD is limited and comparison to a control group in or similar to NYC has not been explored. The objective of this study is to compare FIM scores between a PCP office and a diabetes center in NYC.

Method: Parents of children at a diabetes and PCP office in NYC completed the FIM and Holmes and Rahe Stress Scale (HRSS) to assess stressful events.

Results: Parents of 66 CWD (47% Male) and 97 of a child without (45% Male) (controls) enrolled. Compared to controls, CWD were older (median 13.7 vs. 8.3 years; p<0.0001), included more white subjects (86 vs. 63%; p<0.0001) and scored higher on HRSS (median 128.5 vs. 68; p<0.001). Adjusting for age, sex, race, and HRSS, difference in total FIM scores between groups was statistically significant (p=0.002) with higher impact on the CWD group. Statistically significant differences were found in total Parent Health Related QoL (PHRQoL) (p=0.003), physical function (p=0.0009), cognitive function (p<0.0001), communication (p=0.0003), worry (p<0.0001), and daily activity (p=0.04). None were found in total Family Function, emotional or social function, and family relations.

Conclusion: Results show NYC parents of a CWD have higher levels of family impact compared to a community sample. They have worse PHRQoL stress, worry, cognitive and physical function, communication, and daily activity. It is unknown why there is no difference between the groups in all subscales. Previously we reported having a CWD has impact on, communication if CWD is male, worry if multiple CWD, and cognitive function if additional illness. HbA1c, age, and disease duration were not predictors. It should be noted, families from a diabetes clinic are given support which may buffer stress and being in NYC may increase stress regardless. Future study must recruit a larger sample, create normative data, and explore other illnesses.