The Association Between Obesity and Social Isolation as Well as Loneliness in the Adult Population: A Systematic Review

Figures & data

Table 1 Search Strategy (PubMed)

#	Search Term
#1	Excess weight
#2	Obes*
#3	Adipos*
#4	#1 OR #2 OR #3
#5	Loneliness
#6	Social exclusion
#7	Social isolation
#8	#5 OR #6 OR #7
#9	#4 AND #8

Notes: The number sign (#) refers to the search order. The asterisk (*) is a truncation symbol.

Table 2 Data Extraction

First Author	Country	Assessment of Obesity	Assessment of Loneliness or Social Isolation	Study Type	Sample Description	Sample Size	Age	Females in Total Sample	Results
Hajek (2020a)^Citation17	Germany	BMI > 30 kg/m^2	Revised UCLA Loneliness Scale (three items)	Longitudinal (three waves, 2013–2017)	Survey of Health, Ageing and Retirement in Europe	n=10,446	M=66.0 SD=9.7 50–101	52.1%	According to asymmetric fixed-effects regression, the onset of obesity was associated with a decrease of loneliness among men (ß=−.31, p<0.05) and an increase among women (ß=0.33, p<0.01).
Hajek (2020b)^Citation16	Germany	BMI > 30 kg/m^2	Lubben Social Network Scale (six items)	longitudinal (two waves, 2014/2015 to 2015/2016, 20 months)	Study on Needs, Health Service Use, Costs and Health-Related Quality of Life in a Large Sample of Oldest-Old Primary Care Patients (85+) (AgeQualiDe)	n=675	M=89.6 SD=2.8 85–100	67.9%	Random-effects logistic regression stated that social isolation was not associated with obesity.
Hajek (2018)^Citation21	Germany	BMI > 30 kg/m^2	scale generated by Bude and Lantermann (four items)	cross-sectional	German Ageing Survey	n=7838	M=64.4 SD=11.2 range not specified	51.0%	As linear regression revealed, obesity was related to social exclusion only among women (ß=−0.1, p<0.05).
Hajek (2019)^Citation8	Germany	BMI > 30 kg/m^2	Loneliness scale developed by Gierveld and van Tilburg (six items)	Longitudinal (four waves, 2002–2014)	German Ageing Survey	n=21,099	M=63.4 SD=11.5 range not specified	49.2%	Regarding fixed-effects regression, obesity was positively associated with loneliness among men (ß=0.1, p<0.05), but not among women.
Rotenberg (2017)^Citation18	United Kingdom	BMI > 30 kg/m^2	UCLA-R Loneliness Scale (20 items)	Cross-sectional	Undergraduates from a mid-size university	n=137	M=21.8 SD=4.7 18–57	58.4%	An ANOVA revealed that obesity was associated with increased levels of loneliness (p<0.001).
Sarlio-Lähteenkorva (1999)^Citation19	Finland	BMI > 30 kg/m^2	Feeling lonely (dichotomous)	Cross-sectional	Survey of Living Conditions	n=6,016	M=44.2 SD not specified 15–65	45%	With regard to logistic regression, feeling lonely was not associated with obesity.

Notes: Hajek (2020a):¹⁷ adjusting for age, marital status, income, self-rated health, functional impairment, depressive symptoms and chronic diseases. Hajek (2020b):¹⁶ adjusting for age, gender, education, marital status, visual impairment, hearing impairment, dementia, depression and chronic diseases. Hajek (2018):²¹ adjusting for age, family status, monthly net equivalent income, smoking status, alcohol consumption, frequency of sports activities, self-rated health and chronic diseases. Hajek (2019):⁸ adjusting for age, employment status, family status, frequency of sports activities, depressive symptoms, and number of chronic diseases. Rotenberg (2017):¹⁸ no further adjustments Sarlio-Lähteenkorva (1999):¹⁹ adjusting for employment status, income, marital status and close friends.

Figure 1 PRISMA flow chart.

Note: Adapted from Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):e1000097.²⁵

Table 3 Quality Assessment

Paper Author and Date	Hajek (2018)	Hajek (2019)	Hajek (2020a)	Hajek (2020b)	Rotenberg (2017)	Sarlio-Lähteenkorva (1999)
1. Was the research question or objective in this paper clearly stated?	Yes	Yes	Yes	Yes	Yes	Yes
2. Was the study population clearly specified and defined?	Yes	Yes	Yes	Yes	Yes	Yes
3. Was the participation rate of eligible persons at least 50%?	No (33%)	Not reported	No (mostly 30 to over 50%)	Yes (50.4%)	Not reported	Yes (73%)
4. Were all the subjects selected or recruited from the same or similar populations (including the same time period)? Were inclusion and exclusion criteria for being in the study prespecified and applied uniformly to all participants?	Yes	Yes	Yes	Yes	Yes	Yes
5. Was a sample size justification, power description, or variance and effect estimates provided?	No	No	No	No	No	No
6. For the analyses in this paper, were the exposure(s) of interest measured prior to the outcome(s) being measured? (if not prospective should be answered as “no”, even is exposure predated outcome)	No (cross-sectional)	No (simultaneously)	No (simultaneously)	No (simultaneously)	No (cross-sectional)	No (cross-sectional)
7. Was the timeframe sufficient so that one could reasonably expect to see an association between exposure and outcome if it existed?	No (cross-sectional)	Yes	Yes	Yes	No (cross-sectional)	No (cross-sectional)
8. For exposures that can vary in amount or level, did the study examine different levels of the exposure as related to the outcome (eg, categories of exposure, or exposure measured as continuous variable)?	Dichotomous (different cut-offs were used)	Dichotomous (different cut-offs were used)	Dichotomous	Dichotomous	Dichotomous	Dichotomous
9. Were the exposure measures (independent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?	Yes	Yes	Yes	Yes	Yes	Yes
10. Was the exposure(s) assessed more than once over time?	No	Yes	Yes	Yes	No	No
11. Were the outcome measures (dependent variables) clearly defined, valid, reliable, and implemented consistently across all study participants?	Yes	Yes	Yes	Yes	Yes	Yes
12. Was loss to follow-up after baseline 20% or less?	Not applicable	Not reported	Yes	Yes	Not applicable	Not applicable
13. Were key potential confounding variables measured and adjusted statistically for their impact on the relationship between exposure(s) and outcome(s)?	Yes	Yes	Yes	Yes	No	Yes
Overall quality judgement	Good	Good	Good	Good	Fair	Good

Abbreviations: ANOVA, analysis of variance; BMI, Body Mass Index; COVID-19, coronavirus disease 2019; FIML, full-information maximum likelihood; NIH, National Heart, Lung, and Blood Institute; SD, standard deviation.

Hajek A , König -H-H . Asymmetric effects of obesity on loneliness among older Germans. Longitudinal findings from the Survey of Health, Ageing and Retirement in Europe. Aging Ment Health . 2020;1–5.

 Web of Science ®Google Scholar

Hajek A , Brettschneider C , van der Leeden C , et al. Prevalence and factors associated with obesity among the oldest old. Arch Gerontol Geriatr . 2020;89:104069. doi:10.1016/j.archger.2020.104069 32413689

 PubMed Web of Science ®Google Scholar

Hajek A , König -H-H . The association between obesity and social exclusion in middle-aged and older adults: findings from a nationally representative study in Germany. BMC Geriatr . 2018;18(1):1–7. doi:10.1186/s12877-018-0946-5 29291720

 PubMed Web of Science ®Google Scholar

Hajek A , König HH . Obesity and loneliness. Findings from a longitudinal population‐based study in the second half of life in Germany. Psychogeriatrics . 2019;19(2):135–140. doi:10.1111/psyg.12375 30294939

 PubMed Web of Science ®Google Scholar

Rotenberg KJ , Bharathi C , Davies H , Finch T . Obesity and the social withdrawal syndrome. Eat Behav . 2017;26:167–170. doi:10.1016/j.eatbeh.2017.03.006 28407567

 PubMed Web of Science ®Google Scholar

Sarlio-Lähteenkorva S , Lahelma E . The association of body mass index with social and economic disadvantage in women and men. Int J Epidemiol . 1999;28(3):445–449. doi:10.1093/ije/28.3.445 10405846

 PubMed Web of Science ®Google Scholar

Moher D , Liberati A , Tetzlaff J , Altman DG , Group P . Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med . 2009;6(7):e1000097. doi:10.1371/journal.pmed.1000097 19621072

 PubMed Web of Science ®Google Scholar