How would you interpret the estimated coefficient on the familysz variable

2a. . logit insured selfemp c. age##c . age male married familysz i. degree Iteration 0: log likelihood = -4120. 1852 Iteration 1: log likelihood = -3588.9447 Iteration 2: log likelihood = -3546.9079 Iteration 3: log likelihood = -3546.4726 Iteration 4: log likelihood = -3546.4725 Logistic regression + Number of obs = 8, 135 LR chi2 (10) = 1147.43 Prob > chi2 = 0. 0800 Log likelihood = -3546.4725 Pseudo R2 0. 1392 insured Coefficient Std. err. Z P> |21 [95% conf. interval] selfemp -1. 176106 . 0847397 -13 . 88 0. 080 -1. 342193 -1. 010019 age . 026066 . 0180757 1. 44 0 . 149 -. 0093616 . 0614937 c. age#c. age -6.75e-06 . 0002321 -0.03 0.977 - . 0004616 . 0004481 male -. 283669 06085 -4.66 0. 000 -. 4029329 -. 1644051 married . 9675866 0691796 13 . 99 0. 090 8319971 1. 103176 familysz -. 1073802 . 0191119 -5 . 62 0. 000 - . 1448388 -. 0699216 degree HS diploma 1. 308866 . 0757701 17.27 0. 080 1. 160359 1. 457372 Bachelor's degree 1, 922521 . 1080739 17.79 0. 000 1. 7107 2. 134342 Master's degree 2, 331317 . 194544 11.98 0.080 1. 950018 2. 712616 Ph. D. 2. 606524 . 3771093 6.91 0. 000 1. 867403 3. 345644 _cons -. 6917788 . 3370592 -2. 05 0. 040 -1. 352403 -. 031155