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Table 2 Descriptive statistics of variables (N = 7782)

From: The effect of informal social support on the health of Chinese older adults: a cross-sectional study

Variables

Description

Mean

SD

QWB

Calculated according to the QWB scale and the AHP method

0.778

0.325

SHS

Self-reported subjective health status, “very poor” = 1, “relatively poor” = 2, “fair” = 3, “relatively good” = 4, “very good” = 5

3.376

0.861

ISS

ISS = SE×0.2 + PSS×0.3 + ES×0.5

2.091

1.075

SE

The number of friends respondents could see or communicate with at least once a month, “none” = 0, “only 1” = 1, “only 2” = 2, “3–4” = 3, “5–8” = 4, “9 and more” = 5

2.372

1.277

PSS

The number of friends with whom respondents can communicate or share private matters with confidence, “none” = 0, “only 1” = 1, “only 2” = 2, “3–4” = 3, “5–8” = 4, “9 and more” = 5

2.021

1.139

ES

The number of friends who can provide some help when the respondent is in need, “none” = 0, “only 1” = 1, “only 2” = 2, “3–4” = 3, “5–8” = 4, “9 and more” = 5

2.022

1.231

GEN

“Female” = 0, “Male” = 1

0.508

0.500

AGE

Year surveyed (2018) minus respondents’ birth year

71.189

7.251

EDU

“Not attending school” = 1, “primary school” = 2, “middle school” = 3, “high school/technical secondary school” = 4, “junior college” = 5, “university and above” = 6

2.253

1.042

SPOUSE

“No spouse” = 0, “have a spouse” = 1

0.713

0.453

HUKOU

“Agricultural household registration” = 0, “Non-agricultural household registration” = 1

0.483

0.500

PENS

“None” = 0, “Having participated in Basic endowment insurance for urban employees / endowment insurance for government agencies and institutions / basic endowment insurance for urban and rural residents” = 1

0.794

0.404

PINCO

Total personal income in the past year

8.200

1.412

ACT

The frequency of activity / work in the past week, “never” = 1, “sometimes” = 2, “often” = 3

2.389

0.662

NCHIL

The number of living children

2.5250

1.323

HINCO

The average monthly household income in the past year

9.575

1.254

  1. SD, standard deviation. To mitigate the influence of heteroskedasticity and multicollinearity on the regression results, we perform natural logarithmic transformations on PINCO and HINCO