Table 3.
Multilevel multinomial logit model estimates examining the correlates of multimorbidity
| Variable | One disease versus no disease (95 % CI) | Multimorbidity versus no disease (95 % CI) |
|---|---|---|
| Age | ||
| 18–49 R | ||
| 50–59 | 2.50*** (2.31–2.7) | 5.10*** (4.68–5.58) |
| 60–69 | 3.37*** (3.09–3.71) | 10.75*** (9.73–11.85) |
| 70+ | 4.04*** (3.58–4.52) | 17.96*** (15.90–20.22) |
| Sex | ||
| Male R | ||
| Female | 1.04 (0.98–1.12) | 1.26*** (1.17–1.35) |
| Residence | ||
| Urban R | ||
| Rural | 1.04 (0.97–1.11) | 0.95* (0.88–1.01) |
| Marital status | ||
| Never married R | ||
| Currently married/cohabiting | 1.53*** (1.37–1.72) | 1.59*** (1.41–1.77) |
| Widowed/divorced | 1.74*** (1.54–2.03) | 1.95*** (1.71–2.18) |
| Years of schooling | ||
| No formal schooling R | ||
| 1–5 years | 0.96 (0.87–1.05) | 0.92** (0.83–1.00) |
| 6–9 years | 0.79*** (0.72–0.86) | 0.71*** (0.64–0.77) |
| 10+ years | 0.71*** (0.64–0.77) | 0.53*** (0.48–0.59) |
| Wealth quintile | ||
| Lowest R | ||
| Lower | 1.06 (0.95–1.16) | 1.02 (0.91–1.12) |
| Middle | 1.12** (1.01–1.22) | 1.04 (0.94–1.14) |
| Higher | 1.03 (0.94–1.13) | 0.92* (0.83–1.02) |
| Highest | 1.02 (0.92–1.13) | 0.87*** (0.77–0.96) |
| Waist-hip ratio | ||
| High risk | 1.12*** (1.05–1.19) | 1.34*** (1.26–1.43) |
| Low risk R | ||
| Body mass index | ||
| Obese | 1.58*** (1.39–1.76) | 2.26*** (2–2.52) |
| Not obese R | ||
| Physical activity | ||
| Active R | ||
| Inactive | 1.02 (0.95–1.1) | 1.14*** (1.07–1.23) |
| Daily tobacco consumption | ||
| No R | ||
| Yes | 1.00 (0.93–1.08) | 1.00 (0.93–1.09) |
| Alcohol consumption | ||
| No R | ||
| Yes | 1.14*** (1.04–1.27) | 1.12** (1.01–1.24) |
| Random part | ||
| Country level variance | ||
| Variance (cons_1) | 0.08 (0.02–0.27) | |
| Covariance (cons_1,cons_2) | 0.04 (−0.09 to 0.28) | |
| Variance (cons_2) | 0.25 (0.06–0.85) | |
| Province level variance | ||
| Variance (cons_1) | 0.12 (0.07–0.19) | |
| Covariance (cons_1,cons_2) | 0.19 (0.12–0.3) | |
| Variance (cons_2) | 0.36 (0.24–0.54) | |
R Reference category. * P <0.1, ** P <0.05, *** P <0.01. Estimates are obtained through MCMC algorithm available in MLWin