1. Epidemiology and Global Health

The role of adolescent lifestyle habits in biological aging: A prospective twin study

  1. Anna Kankaanpää  Is a corresponding author
  2. Asko Tolvanen
  3. Aino Heikkinen
  4. Jaakko Kaprio
  5. Miina Ollikainen
  6. Elina Sillanpää
  1. Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Finland
  2. Methodology Center for Human Sciences, University of Jyväskylä, Finland
  3. Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Finland
https://doi.org/10.7554/eLife.80729
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Cite this article
  1. Anna Kankaanpää
  2. Asko Tolvanen
  3. Aino Heikkinen
  4. Jaakko Kaprio
  5. Miina Ollikainen
  6. Elina Sillanpää
(2022)
The role of adolescent lifestyle habits in biological aging: A prospective twin study
eLife 11:e80729.
https://doi.org/10.7554/eLife.80729
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6 figures, 7 tables and 2 additional files

Figures

Figure 1
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Decomposition of (A) total variation in biological aging and (B) the variation of the residual term.
Figure 2 with 1 supplement
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Classes with different lifestyle patterns (n = 5114).

Mean and probability profiles (95% confidence intervals) of the indicator variables utilized in the classification: (A) body mass index, (B) regular leisure-time physical activity (LTPA) (several times a week), (C) daily smoking, and (D) regular alcohol use (once a month or more). For categorical variables, the probabilities of belonging to the highest categories are presented.

Figure 2—source data 1

The estimation results of a latent class analysis (LCA) model with five classes.

https://cdn.elifesciences.org/articles/80729/elife-80729-fig2-data1-v1.xlsx
Figure 2—figure supplement 1
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Lifestyle-related factors in adulthood (21–25 years) according to the adolescent lifestyle behavior classes in the subsample of participants with information on biological aging (n = 824).

(A) Body mass index (BMI), (B) leisure-time physical activity (LTPA), (C) prevalence of daily smokers, and (D) alcohol use. Means and 95% confidence intervals are presented. C1, the class with the healthiest lifestyle; C2, the class with low-normal BMI; C3, the class with healthy lifestyle and high-normal BMI; C4, the class with high BMI; C5, the class with the unhealthiest lifestyle pattern. The model was controlled for sex (female), age, and baseline pubertal development.

Figure 2—figure supplement 1—source data 1

Means and 95% confidence intervals of the lifestyle-related factors in adulthood according to the adolescent lifestyle behavior classes (BCH approach).

https://cdn.elifesciences.org/articles/80729/elife-80729-fig2-figsupp1-data1-v1.xlsx
Figure 3 with 1 supplement
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Mean differences between the adolescent lifestyle behavior patterns in biological aging measured with (A) DNAm PhenoAge, (B) DNAm GrimAge, (C) DunedinPoAm, and (D) DunedinPACE estimators (n = 824).

The analysis was adjusted for sex (female), standardized age, and baseline pubertal development. Means and 95% confidence intervals are presented. C1, the class with the healthiest lifestyle pattern; C2, the class with low-normal body mass index (BMI); C3, the class with a healthy lifestyle and high-normal BMI; C4, the class with high BMI; C5, the class with the unhealthiest lifestyle pattern; AA, age acceleration.

Figure 3—source data 1

Means and 95% confidence intervals of biological aging according to the adolescent lifestyle behavior patterns (BCH approach).

https://cdn.elifesciences.org/articles/80729/elife-80729-fig3-data1-v1.xlsx
Figure 3—figure supplement 1
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DNA methylation (DNAm)-based plasma proteins and smoking pack-years according to the adolescent lifestyle behavior patterns (n = 824).

(A) DNAm adrenomedullin (ADM), (B) DNAm beta-2 microglobulin (B2M), (C) DNAm growth differentiation factor (GDF15), (D) DNAm cystatin C, (E) DNAm leptin, (F) DNAm plasminogen activation inhibitor 1 (PAI-1), DNAm tissue inhibitor metalloproteinase 1 (TIMP-1), and (H) DNAm smoking pack-years (packyrs). Means and 95% confidence intervals are presented. C1, the class with the healthiest lifestyle pattern; C2, the class with low-normal body mass index (BMI); C3, the class with healthy lifestyle and high-normal BMI; C4, the class with high BMI; C5, the class with the unhealthiest lifestyle pattern. The model was controlled for sex (female), age, and baseline pubertal development.

Figure 3—figure supplement 1—source data 1

Means and 95% confidence intervals of DNA methylation (DNAm)-based plasma proteins and smoking pack-years according to the adolescent lifestyle behavior patterns (BCH approach).

https://cdn.elifesciences.org/articles/80729/elife-80729-fig3-figsupp1-data1-v1.xlsx
Figure 4
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Proportions of the total variation in biological aging explained by genetic and (unshared) environmental factors shared with adolescent lifestyle patterns among young adult twin pairs (MZ n = 154, DZ n = 211).

The results are based on the model including additive genetic and non-shared environmental component (AE model). AA, age acceleration.

Figure 4—source data 1

Genetic and environmental factors underlying the association between adolescent lifestyle patterns and biological aging.

https://cdn.elifesciences.org/articles/80729/elife-80729-fig4-data1-v1.xlsx
Author response image 1
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Correlations between epigenetic age acceleration (AA) measures assessed with different clocks.
Author response image 2
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Mean differences between the adolescent lifestyle behavior patterns in biological aging measured with original and PC-based (A) DNAm PhenoAge and (B) DNAm GrimAge.

The analysis was adjusted for sex (female), standardized age and baseline pubertal development. Means and 95% confidence intervals are presented. C1 = the class with the healthiest lifestyle pattern, C2 = the class with low–normal BMI, C3 = the class with a healthy lifestyle and high–normal BMI, C4 = the class with high BMI, C5 = the class with the unhealthiest lifestyle pattern. AA, age acceleration.

Tables

Table 1
Descriptive statistics of the adolescent lifestyle-related variables in all twins and in the subsample of twins with information on biological aging.
All twins (n = 5114)Subsample (n = 824)
nMean (SD) or %nMean (SD) or %
Zygosity4852824
 MZ165034.033540.7
 Same-sex DZ160333.026231.8
 Opposite-sex DZ159933.022727.5
Sex5114824
 Female258450.547057.0
 Male253049.535443.0
At age 12
 Pubertal development (1–3)51111.6 (0.5)8231.6 (0.5)
 Body mass index491317.6 (2.6)79317.7 (2.6)
 Leisure-time physical activity5038813
 Less than once a week187737.329535.3
 Once a week249949.641651.2
 Every day66213.110212.5
At age 14
 Body mass index447319.3 (2.7)78719.5 (2.6)
 Leisure-time physical activity4590799
 Less than once a week68815.011013.8
 Once a week79617.314918.6
 2–5 times a week218247.537046.3
 Every day92420.117021.3
 Smoking status4570800
 Never395486.568785.9
 Former2966.5577.1
 Occasional1222.7243.0
 Daily smoker1984.3324.0
 Alcohol use (binge drinking)4565796
 Never350176.760275.6
 Less than once a month75616.613517
 Once or twice a month2756.0506.3
 Once a week or more330.791.1
At age 17
 Body mass index415821.4 (3.0)76021.4 (2.7)
 Leisure-time physical activity4208766
 Less than once a week74817.813217.2
 Once a week68616.313017.0
 2–5 times a week197747.036347.4
 Every day79718.914118.4
 Smoking status4190762
 Never241957.745459.7
 Former49311.88310.9
 Occasional2135.1486.3
 Daily smoker106525.417623.1
 Alcohol use (binge drinking)4217766
 Never88120.915219.8
 Less than once a month180742.934044.4
 Once or twice a month124029.422229.0
 Once a week or more2896.9526.8

  1. MZ, monozygotic twins; DZ, dizygotic twins; SD, standard deviation.

Table 2
The intraclass correlation coefficients (ICCs) of epigenetic aging measures by zygosity and correlation coefficients between the measures (n = 824).
ICCs (95% CI)Correlation coefficients (95% CI) off-diagonal and means (standard deviations) on the diagonal
MZ twin pairsDZ twin pairsAAHorvathAAHannumAAPhenoAAGrimDunedinPoAmDunedinPACE
AAHorvath0.71 (0.63, 0.79)0.40 (0.24, 0.55)0.00 (3.51)
AAHannum0.66 (0.56, 0.76)0.32 (0.16, 0.48)0.40 (0.33, 0.48)0.00 (3.27)
AAPheno0.69 (0.60, 0.78)0.16 (0.00, 0.33)0.36 (0.29, 0.44)0.61 (0.56, 0.66)0.00 (5.25)
AAGrim0.72 (0.63, 0.80)0.35 (0.15, 0.55)0.08 (0.01, 0.16)0.32 (0.24, 0.40)0.39 (0.33, 0.46)0.00 (3.24)
DunedinPoAm0.62 (0.52, 0.71)0.42 (0.24, 0.60)–0.05 (-0.12, 0.03)0.20 (0.13, 0.27)0.41 (0.35, 0.47)0.57 (0.52, 0.63)1.00 (0.07)
DunedinPACE0.71 (0.64, 0.78)0.46 (0.31, 0.61)–0.04 (–0.11, 0.04)0.30 (0.22, 0.38)0.49 (0.43, 0.55)0.55 (0.49, 0.61)0.62 (0.57, 0.67)0.88 (0.10)

  1. CIs were corrected for nested sampling.

  2. CI, confidence interval; AA, age acceleration; MZ, monozygotic; DZ, dizygotic.

Table 3
Model fit of the latent class models (n = 5114).
AICBICABICVLMRLMRClass sizesAvePP
128842129012128929
122533122880122711<0.001<0.00174.0%, 26.0%0.95, 0.92
119937120460120206<0.001<0.00144.9%, 40.5%, 14.6%0.88, 0.89, 0.93
118030118729118389<0.001<0.00136.4%, 32.7%, 16.7%, 14.2%0.83, 0.86, 0.87, 0.92
1171671180431176170.5290.53032.0%, 22.8%, 19.9%, 15.9%, 9.5%0.78, 0.82, 0.85, 0.88, 0.91
1165261175781170760.1690.17031.5%, 18.5%, 15.7%, 14.0%, 12.7%, 7.7%0.77, 0.84, 0.83, 0.78, 0.78, 0.90
1160991173281167310.0430.04421.0%, 17.5%, 15.2%, 13.8%, 12.9%, 12.8%, 6.9%0.73, 0.82, 0.70, 0.77, 0.83, 0.83, 0.91
1156951171011164180.4070.40820.3%, 16.2%, 13.6%, 13.5%, 12.3%, 11.3%, 9.3%, 3.4%0.72, 0.75, 0.82, 0.71, 0.83, 0.80, 0.82, 0.89

  1. AIC, Akaike’s information criterion; BIC, Bayesian information criterion; ABIC, sample size-adjusted Bayesian information criterion; VLMR, Vuong–Lo–Mendell–Rubin likelihood ratio test; LMR, Lo–Mendell–Rubin-adjusted likelihood ratio test; AvePP, average posterior probabilities for most likely latent class membership.

Table 4
The classes with different adolescent lifestyle behavior patterns (n = 5114).
C1 (32.0%)C2 (19.9%)C3 (22.8%)C4 (9.5%)C5 (15.9%)
Est95% CIEst95% CIEst95% CIEst95% CIEst95% CI
Body mass index
 At age of 12 years16.815.7, 17.915.214.7, 15.719.117.5, 20.722.721.7, 23.817.216.9, 17.5
 At age of 14 years18.617.6, 19.516.716.0, 17.320.919.2, 22.624.823.3, 26.218.918.6, 19.2
 At age of 17 years20.819.7, 22.018.818.1, 19.422.621.6, 23.727.125.0, 29.220.620.3, 20.9
Leisure-time physical activity
 At age of 12 years
 Less than once a week0.290.22, 0.370.450.39, 0.510.350.26, 0.430.440.37, 0.500.440.39, 0.48
 Once a week0.540.48, 0.590.460.41, 0.500.520.47, 0.560.470.39, 0.540.460.41, 0.50
 Every day0.170.14, 0.210.090.04, 0.140.140.07, 0.210.100.06, 0.130.110.08, 0.14
 At age of 14 years
 Less than once a week0.080.05, 0.110.170.12, 0.220.140.07, 0.220.180.13, 0.230.270.22, 0.31
 Once a week0.140.07, 0.200.200.17, 0.240.160.10, 0.230.230.17, 0.280.200.16, 0.23
 2‒5 times a week0.520.45, 0.590.450.41, 0.490.510.43, 0.590.430.37, 0.490.400.35, 0.45
 Every day0.270.23, 0.300.180.13, 0.230.190.12, 0.250.170.12, 0.210.140.10, 0.17
 At age of 17 years
 Less than once a week0.100.05, 0.140.190.14, 0.230.130.06, 0.200.270.19, 0.350.350.29, 0.40
 Once a week0.150.11, 0.180.180.15, 0.210.150.11, 0.190.180.14, 0.230.190.15, 0.23
 2‒5 times a week0.500.44, 0.560.450.41, 0.490.530.48, 0.570.440.36, 0.520.360.32, 0.41
 Every day0.260.22, 0.290.180.13, 0.230.200.12, 0.270.110.07, 0.150.100.07, 0.13
Smoking status
 At age of 14 years
 Never0.990.98, 1.000.980.95, 1.000.970.95, 1.000.830.74, 0.930.330.24, 0.43
 Former0.010.00, 0.020.020.00, 0.030.020.00, 0.040.090.04, 0.140.290.24, 0.34
 Occasional0.000.01–0.01, 0.020.000.00, 0.010.040.01, 0.070.130.10, 0.16
 Daily smoker0.000.000.00, 0.010.000.040.00, 0.070.250.19, 0.31
 At age of 17 years
 Never0.690.61, 0.770.730.65, 0.810.680.59, 0.780.500.41, 0.590.030.00, 0.06
 Former0.120.09, 0.150.090.05, 0.130.120.07, 0.160.110.06, 0.160.150.12, 0.19
 Occasional0.060.04, 0.070.040.02, 0.060.040.01, 0.060.050.02, 0.070.070.05, 0.10
 Daily smoker0.130.08, 0.180.140.09, 0.180.170.09, 0.240.340.24, 0.440.740.69, 0.79
Alcohol use (binge drinking)
 At age of 14 years
 Never0.880.85, 0.910.940.90, 0.970.840.79, 0.890.760.69, 0.830.230.15, 0.31
 Less than once a month0.110.08, 0.140.050.02, 0.080.130.09, 0.170.180.12, 0.240.460.41, 0.51
 Once or twice a month0.010.00, 0.020.020.00, 0.030.030.01, 0.040.050.02, 0.080.270.22, 0.32
 Once a week or more0.000.000.000.000.00, 0.010.040.02, 0.06
 At age of 17 years
 Never0.210.18, 0.250.330.26, 0.410.220.16, 0.280.230.15, 0.300.010.00, 0.02
 Less than once a month0.480.43, 0.520.450.40, 0.490.460.41, 0.520.410.35, 0.470.260.22, 0.31
 Once or twice a month0.280.24, 0.320.180.12, 0.240.280.23, 0.330.290.23, 0.350.510.46, 0.55
 Once a week or more0.030.00, 0.060.040.02, 0.060.030.00, 0.060.080.04, 0.110.220.18, 0.26

  1. Mean and probability profiles of the indicator variables utilized in the classification.

  2. BMI, body mass index; Est, estimated mean or probability; CI, confidence interval; C1, the class with the healthiest lifestyle pattern; C2, the class with low-normal BMI; C3, the class with healthy lifestyle and high-normal BMI; C4, the class with high BMI; C5, the class with the unhealthiest lifestyle pattern.

Table 5
Differences in biological aging between classes with different adolescent lifestyle behavior patterns.
AAPhenoAAGrimDunedinPoAmDunedinPACE
Diff95% CISMDDiff95% CISMDDiff95% CISMDDiff95% CISMD
C2 vs. C1
 M1–0.55–2.15, 1.06–0.10–0.57–1.37, 0.23–0.18–0.01–0.03, 0.01–0.14–0.03–0.05, 0.00–0.30
 M2–0.13–1.79, 1.54–0.02–0.54–1.38, 0.29–0.17–0.01–0.03, 0.01–0.14–0.01–0.04, 0.02–0.10
C3 vs. C1
 M11.04–0.54, 2.630.200.97–0.01, 1.950.300.00–0.02, 0.020.000.02–0.01, 0.040.20
 M20.60–1.01, 2.210.110.94–0.10, 1.970.290.00–0.02, 0.020.000.00–0.03, 0.030.00
C4 vs. C1
 M11.970.44, 3.500.381.830.74, 2.91*0.560.050.03, 0.07*0.710.070.04, 0.11*0.70
 M20.66–1.31, 2.630.131.730.26, 3.210.530.040.01, 0.07*0.570.02–0.02, 0.070.20
C5 vs. C1
 M1–0.36–1.76, 1.04–0.072.701.74, 3.66*0.830.040.02, 0.07*0.570.030.00, 0.060.30
 M2–0.45–1.82, 0.93–0.092.691.73, 3.66*0.830.040.02, 0.06*0.570.030.00, 0.060.30
C3 vs. C2
 M11.59–0.07, 3.250.301.540.58, 2.50*0.480.01–0.01, 0.040.140.040.01, 0.07*0.50
 M20.73–1.10, 2.550.141.480.36, 2.60*0.460.01–0.02, 0.030.140.01–0.03, 0.040.10
C4 vs. C2
 M12.520.85, 4.18*0.482.401.28, 3.51*0.740.070.04, 0.09*1.000.100.06, 0.14*1.00
 M20.79–1.59, 3.160.152.270.59, 3.95*0.700.050.02, 0.09*0.710.03–0.02, 0.080.30
C5 vs. C2
 M10.19–1.40, 1.770.043.272.32, 4.23*1.010.060.03, 0.08*0.860.060.03, 0.09*0.60
 M2–0.32–1.97, 1.33–0.063.242.21, 4.27*1.000.050.03, 0.08*0.710.040.01, 0.070.40
C4 vs. C3
 M10.93–0.82, 2.670.180.85–0.45, 2.160.260.050.03, 0.08*0.710.060.02, 0.10*0.60
 M20.06–1.91, 2.030.010.79–0.68, 2.260.240.050.02, 0.08*0.710.02–0.02, 0.070.20
C5 vs. C3
 M1–1.40–2.99, 0.18–0.271.730.62, 2.84*0.530.040.02, 0.07*0.570.02–0.02, 0.050.20
 M2–1.05–2.63, 0.54–0.201.760.63, 2.88*0.540.050.02, 0.07*0.710.030.00, 0.060.30
C5 vs. C4
 M1–2.33−3.84, –0.82*–0.440.88–0.32, 2.070.27–0.01–0.03, 0.02–0.14–0.04–0.08, 0.00–0.40
 M2–1.10–3.01, 0.80–0.210.96–0.51, 2.440.300.00–0.03, 0.030.000.01–0.04, 0.050.10

  1. AA, age acceleration; BMI, body mass index; Diff, difference; CI, confidence interval; SMD, standardized mean difference; C1, the class with the healthiest lifestyle pattern; C2, the class with low-normal BMI; C3, the class with healthy lifestyle and high-normal BMI; C4, the class with high BMI; C5, the class with the unhealthiest lifestyle pattern; M1, model was adjusted for sex, age, and pubertal status at age 12; M2, model was additionally adjusted for BMI in adulthood.

  2. *

    The corresponding 99% confidence interval did not overlap zero.

Table 6
The estimation results of the univariate model for biological aging among young adult twin pairs (MZ n = 154, DZ n = 211).
Model fitParameter estimates and their 95% confidence intervals
Χ2dfSCpCFITLIRMSEASRMRBICa2/totalc2 or d2/totale2/totalTotal
AAPheno
 ACE5.231.270.1550.980.990.060.0620090.650.56, 0.740.000.350.26, 0.451.000.89, 1.12
 ADE0.630.990.9041.001.020.000.0220030.03–0.46, 0.510.650.15, 1.150.330.25, 0.410.990.88, 1.09
 AE7.040.960.1360.970.990.060.0620030.650.56, 0.74-0.350.26, 0.451.000.89, 1.12
 CE43.540.96<0.0010.600.800.230.112038-0.390.30, 0.480.610.52, 0.700.990.88, 1.10
 E10750.96<0.0010.000.590.330.212093--1.000.990.88, 1.10
AAGrim
 ACE4.332.050.2310.990.990.050.0919890.730.66, 0.800.000.270.20, 0.341.030.87, 1.20
 ADE5.631.550.1330.980.980.070.0919890.640.09, 1.190.09–0.48, 0.660.270.20, 0.341.030.87, 1.19
 AE5.741.540.2200.980.990.050.0919830.730.66, 0.80-0.270.20, 0.341.030.87, 1.19
 CE33.040.87<0.0010.720.860.200.122018-0.500.40, 0.600.500.41, 0.601.020.87, 1.17
 E10451.41<0.0010.060.620.330.262115--1.001.020.87, 1.17
DunedinPoAm
 ACE1.331.120.7221.001.020.000.0420030.520.20, 0.850.09–0.20, 0.370.390.30, 0.480.980.86, 1.11
 ADE1.231.600.7461.001.020.000.0420030.620.53, 0.700.000.380.30, 0.470.980.86, 1.10
 AE1.641.200.8021.001.020.000.0419970.620.53, 0.70-0.380.30, 0.470.980.86, 1.10
 CE12.741.100.0130.880.940.110.072009-0.450.36, 0.550.550.45, 0.640.980.86, 1.10
 E85.151.15<0.0010.000.550.300.222087--1.000.980.86, 1.10
DunedinPACE
 ACE2.031.080.5821.001.000.000.0519980.540.20, 0.870.08–0.21, 0.370.390.30, 0.480.990.87, 1.11
 ADE1.331.680.7400.991.000.000.0519810.42–0.13, 0.970.27–0.31, 0.840.320.24, 0.390.980.84, 1.13
 AE2.141.580.7241.001.100.000.0519760.680.52, 0.82-0.320.24, 0.400.990.84, 1.15
 CE23.741.45<0.0010.760.880.160.102007-0.450.35, 0.540.550.46, 0.650.980.84, 1.13
 E78.551.47<0.0010.090.640.280.232118--1.000.980.84, 1.13

  1. The epigenetic aging measures were adjusted for sex, age, and baseline pubertal development prior to analysis.

  2. SC, scaling correction; CFI, comparative fit index; RMSEA, root mean square error of approximation; SRMR, standardized root-mean-square residual; BIC, Bayesian information criterion; MZ, monozygotic; DZ, dizygotic.

Author response table 1
Means (standard deviations) of the epigenetic age estimates obtained using original and PC-based clocks.
Original clockPC clockPC clock, outliers excluded
Horvath's clock28.9 (3.6)30.8 (3.8)-
Hannum's clock18.2 (3.3)34.4 (4.0)34.4 (3.8)
DNAm PhenoAge13.0 (5.3)16.8 (6.4)16.6 (5.8)
DNAm GrimAge25.2 (3.3)38.8 (3.2)38.8 (3.2)

Additional files

Supplementary file 1

The codes used to analyse the data.

https://cdn.elifesciences.org/articles/80729/elife-80729-supp1-v1.txt
MDAR checklist
https://cdn.elifesciences.org/articles/80729/elife-80729-mdarchecklist1-v1.docx

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  1. Anna Kankaanpää
  2. Asko Tolvanen
  3. Aino Heikkinen
  4. Jaakko Kaprio
  5. Miina Ollikainen
  6. Elina Sillanpää
(2022)
The role of adolescent lifestyle habits in biological aging: A prospective twin study
eLife 11:e80729.
https://doi.org/10.7554/eLife.80729