Sample characteristics
The total sample consisted of 7183 ELSA participants for whom the quality-controlled genome-wide genotyping and BMI during the follow-up were available; of these 46% (N = 3304) were men and 54% (N = 3879) were women. The baseline mean age for men was 64.40 (standard deviation (SD) = 9.15) and for women was 64.35 (SD = 9.56). A larger proportion of men (74.88%) than women (56.17%) reported a longstanding illness (x2 = 6.11, P = 0.011); whereas a larger proportion of women (34.37%) than men (21.35%) showed elevated depressive symptoms (x2 = 148.59, P < 0.001). Men and women differed further in terms of marital status, level of physical activity, income, and educational attainment all reported at baseline (Table 1).
Table 1
Baseline sample characteristics of ELSA participants
Sample Characteristics | Men (n = 3304) | Women (n = 3878) | Test Statistics | |
N(%) / Mean (SD) | N(%) / Mean (SD) | t / x2 | df | P value |
Age (years) | 64.40 (9.15) | 64.35 (9.56) | -0.31 | 7180 | 0.75 |
Source of Baseline BMI | | | | | |
| Wave 2 | 2461 (74.48) | 2937 (75.73) | 1.35 | 1 | 0.25 |
| Wave 4 | 753 (22.79) | 841 (21.68) | | | |
Current Smoker | 512 (15.57) | 653 (16.89) | 2.26 | 1 | 0.13 |
Not married | 780 (23.61) | 1466 (37.79) | 167.06 | 1 | < 0.001 |
Income | | | | | |
| High | 1244 (38.71) | 1207 (32.15) | 49.81 | 2 | < 0.001 |
| Moderate | 997 (31.02) | 1130 (30.10) | | | |
| Low | 973 (30.27) | 1417 (37.75) | | | |
Highest Educational Attainment | | | | | |
| Higher qualification | 1117 (35.80) | 861 (25.04) | 90.02 | 2 | < 0.001 |
| Secondary qualification | 812 (26.03) | 1040 (30.24) | | | |
| Primary qualification | 1191 (38.17) | 1538 (44.72) | | | |
Subjective Social Status | | | | | |
| Top Tertile | 637 (20.33) | 585 (15.90) | 24.35 | 2 | < 0.001 |
| Middle Tertile | 2215 (70.68) | 2780 (75.54) | | | |
| Lower Tertile | 282 (9.00) | 315 (8.56) | | | |
Longstanding Illness present | 1758 (74.88) | 2177 (56.17) | 6.11 | 1 | 0.01 |
Poor Self-Reported Health | 1772 (23.37) | 1 938 (24.18) | 0.64 | 1 | 0.43 |
Physical Activity | | | | | |
| Sedentary | 532 (16.13) | 803 (20.75) | 35.63 | 2 | < 0.001 |
| Moderate activity | 1578 (47.85) | 1878 (48.53) | | | |
| Vigorous activity | 1188 (36.02) | 1189 (30.72) | | | |
Elevated Depressive Symptoms | 704 (21.35) | 1332 (34.37) | 148.59 | 1 | < 0.001 |
Body mass index | | | | | |
| Baselinea | 27.89 (4.27) | 27.97 ( 5.41) | -0.74 | 6990 | 0.45 |
| Wave 6 | 28.11 (4.49) | 28.15 (5.60) | -0.23 | 4331 | 0.82 |
| Wave 8 | 27.88 (4.44) | 27.76 (5.61) | 0.65 | 3212 | 0.51 |
a Combination of BMI measures collected at either wave 2 (for participants where blood was collected for genotyping at wave 2 (77%) and wave 4 (for participants where blood was collected at wave 4 (23%)) |
Educational attainment and BMI-PGS in relation to BMI trajectories
As compared to the group with a higher qualification, having a primary qualification was associated with higher BMI at baseline for women aged ≤ 65 years old (β = 1.25; 95%CI = 0.64–1.85) (Table 2), women aged > 65 years old (β = 1.04; 95%CI = 0.35–1.72) and men aged > 65 years old (β = 0.52; 95%CI = 0.02–1.07) (Table 2). While having a secondary qualification was only associated with a higher BMI at baseline for women aged ≤ 65 years old (β = 1.02; 95%CI = 0.45–1.60). Regarding interaction effects, a 1-SD increase in BMI-PGS was associated with a higher baseline BMI of 0.62 points in men aged > 65 of a secondary education as compared to higher education (β = 0.62; 95% CI = 0.00-1.24) (Fig. 1). For rate of change in BMI, in men aged ≤ 65 years, a secondary (β = 0.06; 95%CI = 0.02–0.10) and primary qualification (β = 0.06; 95%CI = 0.01–0.11) was associated with a steeper increase in BMI across the 12-year follow up.
Table 2
Adjusted longitudinal mixed models exploring the main effect of polygenic score for BMI and educational attainment, and interaction between these two variables, in relation to BMI trajectories during the 12-year follow-up period
| | ≤ 65 Years of Age | > 65 Years of Age |
| | Men | Women | Men | Women |
| | β | 95% CI | β | 95% CI | β | 95% CI | β | 95% CI |
Baseline | | | | | | | | |
| PGS | 1.41*** | 1.10–1.71 | 1.69*** | 1.29–2.10 | 0.57** | 0.25–0.88 | 1.09*** | 0.59–1.59 |
| Higher degree | - | - | - | - | - | - | - | - |
| Secondary qualification | 0.33 | -0.13-0.82 | 1.02*** | 0.45–1.60 | 0.28 | -0.28 -0.86 | 0.39 | -0.40-1.20 |
| Primary qualification | 0.42 | -0.08-0.93 | 1.25*** | 0.64–1.85 | 0.52* | 0.02–1.07* | 1.04** | 0.35–1.72 |
| PGS × Higher qualification | - | - | - | - | - | - | - | - |
| PGS × Secondary qualification | -0.34 | -0.81-0.12 | -0.17 | -0.73-0.37 | 0.62* | 0.09–1.16 | 0.56 | -0.40-1.20 |
| PGS × Primary qualification | -0.19 | -0.68. 0.30 | -0.46 | -1.03-0.12 | 0.34 | -0.11-0.79 | -0.05 | -0.66-0.55 |
Rate of change | | | | | | | | |
| PGS | -0.00 | -0.03-0.02 | -0.01 | -0.02-0.05 | 0.01 | -0.04-0.05 | 0.04 | -0.02-0.10 |
| Higher degree | - | - | - | - | - | - | - | - |
| Secondary qualification | 0.06** | 0.02–0.10 | 0.02 | -0.02-0.07 | 0.07 | 0.00-0.14 | 0.01 | -0.07-0.10 |
| Primary qualification | 0.06** | 0.01–0.11 | 0.05 | -0.00-0.10 | 0.02 | -0.04-0.09 | -0.07 | -0.14-0.01 |
| PGS × Higher degree | - | - | - | - | - | - | - | - |
| PGS × Secondary qualification | 0.01 | -0.02-0.05 | -0.03 | -0.08-0.01 | 0.02 | -0.04-0.08 | -0.03 | -0.12-0.04 |
| PGS × Primary qualification | 0.01 | -0.03-0.06 | 0.01 | -0.04-0.06 | -0.03 | -0.09-0.03 | -0.01 | -0.08-0.06 |
Variance a | | | | | | | | |
| Within-person | 0.04 | 0.03–0.05 | 0.05 | 0.03–0.06 | 0.03 | 0.02–0.07 | 0.04 | 0.02–0.09 |
| In initial status | 15.89 | 14.74–17.13 | 24.44 | 22.78–26.22 | 12.79 | 11.22–14.58 | 20.72 | 18.58–23.12 |
| In rate of change | 0.03 | -0.06-0.11 | 0.01 | -0.11- 0.11 | -0.06 | -0.26-0.14 | 0.15 | -0.04-0.33 |
CI, confidence intervals; PGS, polygenic score; BMI, body mass index
The adjusted models were adjusted for 4 principal components to account for any ancestry differences in genetic structures that could bias the results, as well as; marital status, physical activity level, presence of longstanding limiting illness, self-reported health, depressive symptoms, and smoking status.
a The within-person variance is the overall residual variance in cognition that is not explained by the model. The initial status variance component is the variance of individuals’ intercepts about the intercept of the average person. The rate of change variance component is the variance of individual slopes about the slope of the average person.
× represents an interaction between the two factors; interactions are presented based on multiplicative interaction model
***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05
Subjective Social Status and BMI-PGS in relation to BMI trajectories
As compared to the highest SSS tertile, being in the middle tertile off SSS (β = 0.75; 95%CI = 0.20–1.29) and bottom tertile of SSS (β = 1.16; 95%CI = 0.08–2.24) was associated with a higher BMI at baseline for women aged ≤ 65 years old. However, for men aged ≤ 65 years old, being in the bottom tertile of SSS was associated with a lower BMI at baseline (β=-1.68; 95%CI=-2.55- -0.82) (Fig. 2). In both men and women aged > 65 years old, there was no association between SSS and baseline BMI (Table 3). There was an interaction effect between BMI-PGS and SSS on baseline BMI found for women aged ≤ 65 years old, such that a 1-SD increase in BMI-PGS was associated with lower baseline BMI of 1.41 points for women in the bottom tertile of SSS (β=-1.41; 95%CI=-2.46- -0.36) (Table 3). There were two interaction effects found for change in BMI over time. A Higher BMI-PGS was associated with a reduction in BMI across time for men (aged ≤ 65) in the bottom tertile of SSS as compared to the highest SSS tertile (β =-0.09; 95%CI= -0.17- -0.01) (Table 3). While for women aged > 65 years old, the BMI-PGS was associated with reductions in BMI for those in the bottom tertile of SSS (β=-0.16; 95%CI=-0.32- -0.01).
Table 3
Adjusted longitudinal mixed models exploring the main effect of polygenic score for BMI and subjective social status, and interaction between these two variables, in relation to BMI trajectories during the 12-year follow-up period
| | ≤ 65 Years of Age | > 65 Years of Age |
| | Men | Women | Men | Women |
| | β | 95% CI | β | 95% CI | β | 95% CI | β | 95% CI |
Baseline | | | | | | | | |
| PGS | 1.28*** | 0.87–1.68 | 1.54*** | 1.01–2.01 | 0.52* | 0.10–0.94 | 1.23*** | 0.61–1.84 |
| Top tertile | - | - | - | - | - | - | - | - |
| Middle tertile | -0.33 | -0.81-0.15 | 0.75* | 0.20–1.29 | 0.05 | -0.49-0.60 | 0.37 | -0.35-1.09 |
| Bottom tertile | -1.68*** | -2.55- -0.82 | 1.16* | 0.08–2.24 | 0.44 | -0.45-1.35 | 0.37 | -0.74-1.47 |
| PGS × Top tertile | - | - | - | - | - | - | - | - |
| PGS × Middle tertile | -0.02 | -0.49-0.45 | 0.01 | -0.45-0.62 | 0.42 | -0.06-0.92 | -0.06 | -0.75-0.62 |
| PGS × Bottom tertile | 0.41 | -0.44-1.26 | -1.41** | -2.46- -0.36 | 0.64 | -0.45-1.41 | 0.20 | -0.91-1.31 |
Rate of change | | | | | | | | |
| PGS | 0.03 | -0.01-0.07 | 0.01 | -0.03-0.05 | 0.03 | -0.00-0.08 | 0.08 | -0.02-.18 |
| Top tertile | - | - | - | - | - | - | - | - |
| Middle tertile | 0.03 | -0.02-0.08 | -0.02 | -0.07-0.03 | -0.03 | -0.09-0.03 | 0.01 | -0.09-0.11 |
| Bottom tertile | 0.02 | -0.08-0.11 | 0.03 | -0.06-0.12 | -0.01 | -0.14-0.12 | -0.08 | -0.24-0.07 |
| PGS × Top tertile | - | - | - | - | - | - | - | - |
| PGS × Middle tertile | -0.03 | -0.07-0.01 | 0.00 | -0.04-0.05 | -0.04 | -0.08-0.01 | -0.06 | -0.17 -0.04 |
| PGS × Bottom tertile | -0.09* | -0.17- -0.01 | -0.01 | -0.12-0.10 | -0.01 | -0.10-0.09 | -0.16* | -0.33- -0.07 |
Variance a | | | | | | | | |
| Within-person | 0.05 | 0.03–0.06 | 0.05 | 0.03–0.06 | 0.03 | 0.02–0.07 | 0.04 | 0.03–0.09 |
| In initial status | 15.80 | 14.27–17.50 | 25.11 | 22.92–27.49 | 12.93 | 11.34–14.73 | 21.14 | 19.05–23.45 |
| In rate of change | 0.05 | -0.10-0.20 | -0.03 | -0.18-0.12 | -0.06 | -0.26-0.13 | 0.13 | -0.06-0.32 |
CI, confidence intervals; PGS, polygenic score; BMI, body mass index
The adjusted models were adjusted for 4 principal components to account for any ancestry differences in genetic structures that could bias the results, as well as; marital status, physical activity level, presence of longstanding limiting illness, self-reported health, depressive symptoms, and smoking status. Adjusted models used robust standard errors to relax the assumption that standard errors carried identical and equal distributions, due to the presence of heteroscedascity.
a The within-person variance is the overall residual variance in cognition that is not explained by the model. The initial status variance component is the variance of individuals’ intercepts about the intercept of the average person. The rate of change variance component is the variance of individual slopes about the slope of the average person.
× represents an interaction between the two factors; interactions are presented based on multiplicative interaction model
***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05
Income and BMI-PGS in relation to BMI trajectories
Compared with the highest income tertile, women who were aged > 65 years old in the intermediate (β = 0.81, 95%CI = 0.09–1.53) and lowest income tertiles groups (β = 0.86, 95%CI = 0.18- -1.53) had higher baseline BMI values (Table 4). While for men aged > 65 years old, the intermediate income tertile showed lower baseline BMI values (β=-0.67, 95%CI=-1.21- -0.13). There was an interaction effect between BMI-PGS and income for BMI at baseline for men aged ≤ 65, such that a 1-SD increase in BMI-PGS was associated with a lower baseline BMI value of 0.72 points for men in the lowest tertile of income but not in the highest (β=-0.72, 95%CI=-1.21- -0.23) (Table 4). There were no significant direct effects or interaction effects of income on the rate of change in BMI over the 12-year follow up for either men or women.
Table 4
Adjusted longitudinal mixed models exploring the main effect of polygenic score for BMI and income, and interaction between these two variables, in relation to BMI trajectories during the 12-year follow-up period
| | ≤ 65 Years of Age | > 65 Years of Age |
| | Men | Women | Men | Women |
| | β | 95% CI | β | 95% CI | β | 95% CI | β | 95% CI |
Baseline | | | | | | | | |
| PGS | 1.41*** | 1.12–1.69 | 1.52*** | 1.17–1.85 | 0.85*** | 0.47–1.22 | 1.33*** | 0.75–1.91 |
| High income | - | - | | | - | - | - | - |
| Intermediate income | 0.09 | -0.36-0.56 | 0.51 | -0.04-1.06 | -0.67* | -1.21- -0.13 | 0.81* | 0.09–1.53 |
| Low income | -0.39 | -0.91-0.13 | 0.55 | -0.02- 1.13 | -0.35 | -0.87-0.18 | 0.86* | 0.18–1.48 |
| PGS × High income | - | - | - | - | - | - | - | - |
| PGS × Intermediate income | 0.17 | -0.29-0.63 | 0.14 | -0.41-0.69 | -0.09 | -0.61-0.43 | -0.24 | -1.01-0.51 |
| PGS × Low income | -0.72** | -1.21- -0.23 | -0.22 | -0.78-0.33 | 0.22 | -0.28-0.73 | -0.17 | -0.84-0.50 |
Rate of change | | | | | | | | |
| PGS | -0.00 | -0.02-0.02 | 0.01 | -0.01-0.04 | 0.01 | -0.02-0.05 | -0.02 | -0.09-0.06 |
| High income | - | - | - | -- | - | - | - | - |
| Intermediate income | 0.03 | -0.01-0.08 | 0.03 | -0.02-0.07 | 0.05 | -0.01-0.12 | -0.03 | -0.08-0.08 |
| Low income | 0.03 | -0.02-0.08 | 0.03 | -0.01-.08 | 0.06 | -0.00-0.12 | -0.04 | -0.12-0.04 |
| PGS × High income | - | - | | | - | - | - | - |
| PGS × Intermediate income | 0.00 | -0.04-0.04 | -0.04 | -0.08-0.01 | 0.01 | -0.06-0.07 | 0.06 | -0.03-0.15 |
| PGS × Low income | 0.01 | -0.03-0.06 | 0.02 | -0.02-0.08 | -0.03 | -0.09-0.03 | 0.04 | -0.05-0.13 |
Variance a | | | | | | | | |
| Within-person | 0.04 | 0.03–0.05 | 0.05 | .04-0.06 | 0.03 | 0.02–0.07 | 0.04 | 0.02–0.08 |
| In initial status | 16.02 | 14.88–17.25 | 25.22 | 23.57–26.99 | 13.59 | 11.33–14.67 | 20.95 | 18.95–23.16 |
| In rate of change | 0.06 | -0.02-.14 | -0.04 | -0.15-0.07 | 0.07 | -0.02-0.15 | -0.02 | -0.12-0.08 |
CI, confidence intervals; PGS, polygenic score; BMI, body mass index |
The adjusted models were adjusted for 4 principal components to account for any ancestry differences in genetic structures that could bias the results, as well as; marital status, physical activity level, presence of longstanding limiting illness, self-reported health, depressive symptoms, and smoking status.
a The within-person variance is the overall residual variance in cognition that is not explained by the model. The initial status variance component is the variance of individuals’ intercepts about the intercept of the average person. The rate of change variance component is the variance of individual slopes about the slope of the average person.
× represents an interaction between the two factors; interactions are presented based on multiplicative interaction model
***p ≤ 0.001, **p ≤ 0.01, *p ≤ 0.05
Sensitivity analyses
Upon imputation, we observed that as compared to a higher qualification, men with a primary level education had a higher BMI at baseline in both the > 65 age group (β = 0.51; 95%CI = 0.08–1.11) and ≤ 65 age group (β = 0.49; 95%CI = 0.00–0.98) (Supplementary Table 3). For SSS, the interaction between BMI-PGS and the bottom tertile of SSS on rate of change in BMI in men aged > 65 uncovered in the main analyses was attenuated towards null. Moreover, women aged ≤ 65 and in the lowest tertile of SSS, no longer showed higher BMI at baseline (Supplementary Table 4). For income, women aged ≤ 65 and in the mid and lower income tertiles did not show higher BMI at baseline as in the main analyses (Supplementary Table 5).