| Literature DB >> 23176713 |
M Jokela1, M Hintsanen, C Hakulinen, G D Batty, H Nabi, A Singh-Manoux, M Kivimäki.
Abstract
Personality is thought to affect obesity risk but before such information can be incorporated into prevention and intervention plans, robust and converging evidence concerning the most relevant personality traits is needed. We performed a meta-analysis based on individual-participant data from nine cohort studies to examine whether broad-level personality traits predict the development and persistence of obesity (n = 78,931 men and women; mean age 50 years). Personality was assessed using inventories of the Five-Factor Model (extraversion, neuroticism, agreeableness, conscientiousness and openness to experience). High conscientiousness - reflecting high self-control, orderliness and adherence to social norms - was associated with lower obesity risk across studies (pooled odds ratio [OR] = 0.84; 95% confidence interval [CI] = 0.80-0.88 per 1 standard deviation increment in conscientiousness). Over a mean follow-up of 5.4 years, conscientiousness predicted lower obesity risk in initially non-obese individuals (OR = 0.88, 95% CI = 0.85-0.92; n = 33,981) and was associated with greater likelihood of reversion to non-obese among initially obese individuals (OR = 1.08, 95% CI = 1.01-1.14; n = 9,657). Other personality traits were not associated with obesity in the pooled analysis, and there was substantial heterogeneity in the associations between studies. The findings indicate that conscientiousness may be the only broad-level personality trait of the Five-Factor Model that is consistently associated with obesity across populations.Entities:
Keywords: Longitudinal analysis; meta‐analysis; obesity; personality
Mesh:
Year: 2012 PMID: 23176713 PMCID: PMC3717171 DOI: 10.1111/obr.12007
Source DB: PubMed Journal: Obes Rev ISSN: 1467-7881 Impact factor: 9.213
Characteristics of included studies
| ADDHEALTH | BHPS | GSOEP | HILDA | HRS | MIDUS | NCDS | WLSG | WLSS | |
|---|---|---|---|---|---|---|---|---|---|
| Number of participants | |||||||||
| Cross-sectional analysis | 4,957 | 7,738 | 18,387 | 9,434 | 13,716 | 5,997 | 8,330 | 6,515 | 3,857 |
| Longitudinal analysis | – | – | 12,258 | 7,646 | 12,452 | 3,559 | – | 5,082 | 2,641 |
| Age | 29.0 (1.8) | 46.6 (17.5) | 47.4 (17.3) | 44.7 (17.7) | 67.3 (10.4) | 46.9 (12.9) | 50.3 (0.5) | 54.1 (0.5) | 53.1 (7.3) |
| Sex | |||||||||
| Men | 45.9 (2,275) | 50.7 (3,921) | 47.9 (8,807) | 47.1 (4,440) | 41.2 (5,648) | 48.0 (2,876) | 48.9 (4,073) | 46.9 (3,053) | 47.3 (1,825) |
| Women | 54.1 (2,682) | 49.3 (3,817) | 52.1 (9,580) | 52.9 (4,994) | 58.8 (8,068) | 52.0 (3,121) | 51.1 (4,257) | 53.1 (3,462) | 52.7 (2,032) |
| Education | |||||||||
| Primary | 33.6 (1,664) | 28.6 (2,212) | 16.2 (2,817) | 34.0 (3,212) | 18.5 (2,537) | 8.7 (518) | 18.2 (1,519) | – | 5.1 (197) |
| Secondary | 53.5 (2,651) | 56.6 (4,383) | 61.2 (10,670) | 44.1 (4,158) | 55.2 (7,563) | 59.1 (3,536) | 61.8 (5,146) | 72.0 (4,692) | 64.0 (2,470) |
| Tertiary | 13.0 (642) | 14.8 (1,142) | 22.6 (3,938) | 21.9 (2,064) | 26.3 (3,601) | 32.3 (1,930) | 20.0 (1,665) | 28.0 (1,823) | 30.9 (1,190) |
| Follow-up time (months) | – | – | 48.1 (1.6) | 48.0 (1.3) | 35.4 (16.0) | 107.5 (6.3) | – | 134.0 (4.2) | 135.8 (6.6) |
| Marital status | |||||||||
| Married/cohabiting | 41.5 (2,056) | 55.3 (4,277) | 60.2 (11,063) | 61.2 (5,775) | 64.0 (8,777) | 67.9 (4,069) | 70.3 (5,852) | 83.2 (5,419) | 80.9 (3,093) |
| Single | 58.5 (2,901) | 44.7 (3,460) | 39.8 (7,324) | 38.8 (3,659) | 36.0 (4,937) | 32.1 (1,925) | 29.7 (2,478) | 16.8 (1,096) | 19.1 (732) |
| Baseline obesity | |||||||||
| Non-obese | 63.1 (3,129) | 76.2 (5,893) | 84.0 (15,437) | 79.2 (7,469) | 69.1 (9,480) | 80.9 (4,850) | 75.9 (6,319) | 81.8 (5,327) | 82.1 (3,167) |
| Obese | 36.9 (1,828) | 23.8 (1,845) | 16.0 (2,950) | 20.8 (1,965) | 30.9 (4,236) | 19.1 (1,147) | 24.1 (2,011) | 18.2 (1,188) | 17.9 (690) |
| Follow-up obesity | |||||||||
| Non-obese | – | – | 81.4 (10,440) | 76.7 (5,865) | 69.9 (8,710) | 71.9 (2,564) | – | 75.0 (3,811) | 75.9 (2,004) |
| Obese | – | – | 18.6 (2,383) | 23.3 (1,781) | 30.1 (3,756) | 28.1 (1,002) | – | 25.0 (1,271) | 24.1 (637) |
| Ethnicity/nationality | |||||||||
| Majority | 71.9 (3,564) | 87.9 (6,799) | 93.0 (17,107) | 86.5 (8,156) | 78.0 (10,696) | 89.3 (5,358) | 98.0 (8,162) | 100.0 (6,515) | 100.0 (3,857) |
| Minority | 28.1 (1,393) | 12.1 (939) | 7.0 (1,280) | 13.5 (1,278) | 22.0 (3,020) | 10.7 (639) | 2.0 (168) | – | – |
Note: Because of missing data in covariates, numbers of covariate frequencies may not add up to the total number of participants with personality data.
ADDHEALTH, National Longitudinal Study of Adolescent Health; BHPS, British Household Panel Survey; GSOEP, German Socio-Economic Panel Study; HILDA, Household, Income and Labour Dynamics in Australia; HRS, Health and Retirement Study; MIDUS, Midlife in the United States; NCDS, National Child Development Study; WLSG, Wisconsin Longitudinal Study Graduate Sample; WLSS, Wisconsin Longitudinal Study Sibling Sample.
Figure 1Cross-sectional associations between Five-Factor Model personality traits and obesity at baseline. Values are odds ratios per 1 standard deviation increment in personality trait. Personality traits are adjusted for each other in addition to sex, age and race/ethnicity. Studies are listed in decreasing order of study-specific obesity prevalence. ADDHEALTH, National Longitudinal Study of Adolescent Health; BHPS, British Household Panel Survey; GSOEP, German Socio-Economic Panel Study; HILDA, Household, Income and Labour Dynamics in Australia; HRS, Health and Retirement Study; MIDUS, Midlife in the United States; NCDS, National Child Development Study; WLSG, Wisconsin Longitudinal Study Graduate Sample; WLSS, Wisconsin Longitudinal Study Sibling Sample.
Longitudinal associations between baseline conscientiousness and subsequent obesity risk
| All | Non-obese at baseline | Obese at baseline | |
|---|---|---|---|
| Individual cohorts | |||
| GSOEP | 0.93 (0.87, 1.00) | 0.91 (0.83, 0.99) | 0.97 (0.86, 1.10) |
| WLSS | 0.87 (0.77, 0.99) | 0.85 (0.74, 0.98) | 0.99 (0.76, 1.30) |
| WLSG | 0.88 (0.80, 0.96) | 0.86 (0.78, 0.95) | 0.94 (0.78, 1.14) |
| MIDUS | 0.93 (0.83, 1.03) | 0.91 (0.81, 1.02) | 0.99 (0.78, 1.26) |
| HILDA | 0.91 (0.84, 0.99) | 0.91 (0.82, 1.02) | 0.91 (0.79, 1.05) |
| HRS | 0.88 (0.81, 0.94) | 0.86 (0.77, 0.96) | 0.89 (0.80, 0.99) |
| Pooled | 0.90 (0.87, 0.93) | 0.89 (0.85, 0.92) | 0.93 (0.88, 0.99) |
| 43,638 | 33,981 | 9,657 |
Note: Values are standardized odds ratios (and 95% confidence intervals) adjusted for baseline obesity status, the other four personality traits, educational level, sex, age, follow-up length, ethnicity/nationality. The pooled estimate was calculated using random-effect meta-analysis. See Supporting Information Figures S2–S4 for details.
ADDHEALTH, National Longitudinal Study of Adolescent Health; BHPS, British Household Panel Survey; GSOEP, German Socio-Economic Panel Study; HILDA, Household, Income and Labour Dynamics in Australia; HRS, Health and Retirement Study; MIDUS, Midlife in the United States; NCDS, National Child Development Study; WLSG, Wisconsin Longitudinal Study Graduate Sample; WLSS, Wisconsin Longitudinal Study Sibling Sample.
Figure 2Baseline obesity predicting personality change in conscientiousness between baseline and follow-up wave (combined n = 39,320). Values are standardized regression coefficients for conscientiousness change (standardized with the baseline conscientiousness level within each sample, standard deviation = 1). Mean change gives the average change in conscientiousness in the sample. GSOEP, German Socio-Economic Panel Study; HILDA, Household, Income and Labour Dynamics in Australia; HRS, Health and Retirement Study; MIDUS, Midlife in the United States; WLSG, Wisconsin Longitudinal Study Graduate Sample; WLSS, Wisconsin Longitudinal Study Sibling Sample.