Obesity in Older Adults: Epidemiology and Implications for Disability and Disease (original) (raw)
. Author manuscript; available in PMC: 2013 Feb 1.
Published in final edited form as: Rev Clin Gerontol. 2012 Feb 1;22(1):10–34. doi: 10.1017/s0959259811000190
Summary
Obesity is a worldwide problem with increasing prevalence and incidence in both developed and developing countries. In older adults, excess weight is associated with a higher prevalence of cardiovascular disease, metabolic disease, several important cancers, and numerous other medical conditions. Obesity has been also associated with increased functional limitations, disability, and poorer quality of life. Additionally, obesity has been independently associated with all-cause mortality. The obesity epidemic has important social and economic implications, representing an important source of increased public health care costs. The aim of this review is to report the epidemiology of obesity world-wide and the implications of obesity on disability and chronic diseases.
Keywords: Obesity, Older Adults, Disability, Chronic Disease
Obesity is a health concern in both developed and developing countries. Numerous studies have documented an increase in the prevalence of obesity worldwide, a trend that has been described as an “epidemic”. Increases in the prevalence of obesity have been observed in men and women, in all age groups, in all major ethnic groups, and at all educational levels. According to the World Health Organization (WHO), obesity prevalence has doubled since 1980 1. Some authors argue that up to one third of the life expectancy gains over time attributable to public health achievements, such as reductions in smoking are counteracted by the simultaneous increase in obesity prevalence 2;3. Among older adults, obesity has been related to higher rates of disability and poor overall health 4. This is especially relevant given the expected worldwide growth of older adult populations.
We searched Medline, PubMed, EMBASE and World of Science databases and websites for the World Health Organization, and for major longitudinal studies on ageing such as the English Longitudinal Study on Ageing (ELSA) [http://www.esds.ac.uk/longitudinal/access/elsa/] the Survey of Health, Ageing and Retirement in Europe (SHARE) [http://www.share-project.org/], the Health and Retirement Study (HRS) [http://hrsonline.isr.umich.edu/], The Health, Well-Being, and Ageing Survey (SABE). We did not limit the search by type of study given the complexity of the topics addressed; however, we did limit the search to manuscripts published in core clinical and epidemiological journals between 1991 and 2011, given the focus of the review. Our initial search terms included ‘obesity’, ‘prevalence’, ‘trends’, ‘older adults’ and ‘epidemiology’. We went on to conduct several further searches to find articles related to obesity and disability and obesity and chronic diseases for each of the sub-sections covered in this article.
Epidemiology of Obesity around the World
Comparisons between regions around the world indicate a wide variation in prevalence of obesity. Despite these regional differences, over time the prevalence of obesity has increased worldwide 1. Table 1 summarizes the prevalence of obesity according to studies published in the last two decades using information from three regions in the world: North America (USA and Canada), Latin America and Europe.
Table 1.
Summary of literature review of studies reporting prevalence of obesity around the world in the past two decades.
| Author | Year | Age Inclusion | Type of Study | BMI cut-offpoints | Mean BMI or prevalence | Region | Notes |
|---|---|---|---|---|---|---|---|
| MacDonald,SM14 | 1997 | 18 -74 y/o | Cross sectional surveysconducted in ten Canadianprovinces between 1986 -1992 | Obesityconsideredas BMI ≥ 27 | Mean BMI for men was 25.8(SD 4.03) and 24.9 (SD 5.14)for women. A total of 35% ofmen and 27% of women wereconsidered to be obese. | North America | Additional study conducted withsame dataset by the same groupreported no differences in BMIbetween urban and rural areas ofCanada |
| Torrance,GM13 | 2002 | 20 - 69 y/o | Cross sectional study usingthree different nationalsurveys to determine trendin obesity of adults inCanada. | WHO cut-points | Prevalence of obesity increasedover time for men from 8.1%(1970-72) to 12% (1978-79) to13.4 (1986-1992). Similarly forwomen the prevalenceincreased from 12.7% (1970-72)to 14.9% (1978-79) to 15.4(1986-1992). | North America | No differences observed byeducation, however smokingstatus had a strong relationshipwith increasing obesity trends. |
| Kaplan, MS12 | 2003 | ≥ 65 y/o | Cross sectional study usingwave 2 (1996-1997) of theCNPHS survey | WHO cut-points | A total of 12.8% of older adultsfell under the obese category | North America | Overall, men were 37% more likelyto be obese than women. Obesitywas also more common amongyounger senior adults; lesseducated; unmarried; nonsmokers;infrequent and heavier alcoholusers; physically inactive; morecomorbidities; functionallimitations; poorer self-ratedhealth; and reporting psychologicaldistress. Place of birth alsopredicted obesity. |
| Crimmins, E7 | 2005 | ≥ 65 y/o | Longitudinal | WHO cut-points | Prevalence increased from21.4% (1988-1994) to 30.8%(1999-2000) | North America | NHANES III and IV data |
| Ford, ES9 | 2009 | 25 to 74 y/o | Cross-sectional | WHO cut-points | Age adjusted prevalence ofobesity: 11.1[1971-1975]; 10.9[1976-1980]; 15.5 [1988-1994];19.3 [1999-2004] | North America | NHANES |
| Bleich, SN5 | 2009 | ≥ 20 y/o | Cross sectional | WHO cut-points | Prevalence of obesity reportedat 22% [1988-1994] and 31%[1999-2004] | North America | NHANES. Examines relationshipbetween increased consumption ofsugar-sweetened beverages withincreasing prevalence of obesity |
| Lix, LM16 | 2009 | ≥ 20 y/o | Cross sectional study using2 waves of the CCHS(2000-2001 and 2005-2006) | WHO cut-points | At baseline 20% of thepopulation was obese. Betweenbaseline and follow up therewas an increase in prevalenceof obesity but only for Aboriginalparticipants. Prevalence ofobesity at baseline forAboriginals was 20.2% (95% CI18.1-22.4) and 18.5% (95% CI15.9-21.0) for Non-Aboriginals.At follow-up the prevalence was25.4 %( 95% CI 20.5-30.2) and21.1 %( 18.3-23.9) forAboriginals and Non-Aboriginalsrespectively. | North America | Cover three regions of northernCanada. Variations in prevalenceof obesity observed by ethnicgroup and region. |
| Cohen, JD6 | 2010 | 20 to 74 y/o | Analysis of trend using datafrom NHANES I, II and III | WHO cut-points | Mean BMI for each cross-section: 25.5(±5.0) [1976-1980];27.3(±5.9) [1988-1994];28.7(±6.6) [1999-2006].Prevalence of obesity for eachcross-section: 15%[1976-1980],26% [1988-1994] and 34%[1999-2006]. | North America | NHANES 1976-2006 data.Examined trends in serum lipids asmain outcome. Only individualswith 1 or more total cholesterol orlipid results were included. |
| Flegal, KM8 | 2010 | ≥ 20 y/o | Analysis of trends usingcross-sectional data fromNHANES between 1999-2000 and 2007-2008 | WHO cut-points | In 2007-2008 the age adjustedprevalence of obesity was33.8% (95% CI 31.6%-63.0%).For men it was 32.2% (95% CI29.5-35.0) and for women35.5% (95% CI 33.2-37.7). | North America | Differences observed by genderand race/ethnicity. Between 1999-2000 and 2007-2008 a 4.7%increase in obesity for men and2.1% increase for women wereobserved. Prevalence change forwomen was not significant.Prevalence of overweight andobesity was 68%. |
| Stenholm, S11 | 2010 | ≥ 60 y/o | Longitudinal study inBaltimore | WHO cut-points | Mean BMI for men of threedifferent cohorts from the BLSAstudy: 24.2(±3) [1877-1899];25.2(±3.2) [1900-1919];27.5(±4.3) [1920-1943] | North America | Secular increase in bodyweight inthree cohorts of older white men inthe US independent of bodyheight. BLSA study |
| Ford, ES10 | 2011 | ≥ 20 y/o | Analysis of trends usingcross-sectional databetween 1999-2000 and2007-2008 | WHO cut-points | Age adjust mean BMI for men26.9 in 1999-2000 and 32% in2007-2008; In women 33.2% in1999-2000 and 35.2 in 2007-2008 | North America | Analyzes trends in obesity andabdominal obesity using NHANESdata |
| Bruce, SG15 | 2010 | ≥ 18 y/o | Cross Sectional study usingdata from an Aboriginalgroup in Canada | WHO cut-points | A total of 56% of the samplewere obese. A total of 50% ofmen and 65% of women wereobese. | North America | Analyses one group of Aboriginal.Aboriginals in Canada areconsidered to have poorer overallhealth compared to other ethnicgroups in Canada. |
| Ruiz-Arregui,L19 | 2005 | ≥ 60 y/o | Cross sectional study usingthe first wave (2001) of theMHAS | WHO cut-points | Obesity was present in 20.9% ofthe total population. A total of24.8% of women and 17.3% ofmen were obese. | Latin America | Hypertension and limitations inwalking were associated to higherprevalence of obesity |
| Monteiro, CA18 | 2007 | ≥ 20 y/o | Uses cross sectional datafrom 3 national surveys inBrazil (1975, 1989, 2003) toestimate trends in Obesity | WHO cut-points | Mean BMI Men: 22.4 SE 0.08[1975], 23.5 SE 0.07 [1989],24.6 SE 0.04 [2003]. Mean BMIWomen: 23.0 SE 0.08 [1975],24.5 SE 0.07 [1989], 24.7 SE0.04 [2003]. Prevalence ofobesity was 2.7% in 1975, 5.1%in 1989 and 8.8% in 2003 formen and 7.4%, 12.4% and 13%for women in the same years. | Latin America | Obesity trends in men increasedbut in women remained the samebetween 1989 and 2003 comparedto 1975-1989. Increases in obesitywere more prevalent in lower SESquintiles for both men and women. |
| Al Snih, S44 | 2010 | ≥ 65 y/o | Cross sectional study usingdata from the SABE studythat included 6 cities in LatinAmerica and the Caribbean | WHO cut-points,separatescategory I(BMIbetween 30and 34.9)fromcategory IIand extremeobesity (BMI≥ 35) | Mean BMI for the different cities:Bridgetown, Barbados 26.9(95% CI 26.4-27.3); Sao Paolo,Brazil 26.4 (95% CI 26.1-26.7);Santiago, Chile 27.7 (95% CI27.2-28.2); Havana, Cuba 24.2(95% CI 23.9-24.5); MexicoCity, Mexico 27.5 (95% CI 27.1-27.8); Montevideo, Uruguay28.3 (95% CI 27.9, 28.8). Theprevalence of category I obesitywas: Bridgetown, Barbados15.2% (95% CI 13.1-17.4); SaoPaolo, Brazil 17.6 (95% CI 15.5-19.8); Santiago, Chile 22.9%(95% CI 20.1-25.8); Havana,Cuba 10.4% (95% CI 8.4-12.4);Mexico City, Mexico 21.3%(95% CI 18.2-24.4);Montevideo, Uruguay 21.9%(18.5-25.3). The range forcategory II and extreme obesitywas between 2.9% and 15.7%. | Latin America | Obesity is an independent factorcontributing to ADL disability.Category I and Category II obesityare presented separately. Weadded both percentages to reportprevalence of obesity overall. |
| Morabia, A26 | 2005 | 35-74 y/o | Cross-sectional yearlyinterviews of people inSwitzerland between 1993-2003 | WHO cut-points | Prevalence of obesity increasedfrom 9% in 1993 to 15% in 2003in men; in women it increasedfrom 7% to 11%. | Europe | Age adjusted trends. |
| Andreyeva, T21 | 2007 | ≥ 50 y/o | Cross sectional data studyusing data from the firstwave of SHARE (2004) apanel study including elevencountries in Europe. | WHO cut-points | Obesity was present in 16.2% ofmen and 17.8% of women. Theprevalence for each country wasas follows: 17.9% in Austria,14%in Denmark, 15.1% inFrance, 16.9% in Germany,16.8% in Greece, 15.2% in Italy,13% in the Netherlands, 20.2%in Spain, 12.8% in Sweden,13% in Switzerland; for womenthe prevalence was: 19.7% inAustria, 13.3%in Denmark,15.1% in France, 17.4% inGermany, 21.9% in Greece,17.1% in Italy, 16.5% in theNetherlands, 25.6% in Spain,14.4% in Sweden, 12.3% inSwitzerland | Europe | |
| Charles, MA22 | 2008 | ≥ 18 y/o | Uses cross sectional datafrom 4 national surveys inFrance (1997, 2000, 2003,2006) to examine trends inobesity | WHO cut-points | Prevalence of obesity increasedfrom 8.6% (95% CI 8.2-8.8) in1997 to 13.1% (95% CI 12.7-13.5) in 2006. | Europe | Parallel increase in obesity trendsfor men and women between1997-2003 but slightly lower inmen between 2003-2006. |
| Lang, IA25 | 2008 | ≥ 65 y/o | Longitudinal study usingdata from ELSA to predictmortality and disability byBMI status | WHO cut-points | Prevalence of obesity atbaseline was 19.4% for menand 28.9% for women. | Europe | Obesity at baseline was related tohigher risk of mortality anddisability. |
| Kotseva, K20 | 2009 | <= 70 y/o | Cross sectional study usingEUROASPIRE I,II and IIIdata | WHO cut-points | Age and diagnosis adjusted:25% [95-96]; 32.6% [99-00];38% [06-07] | Europe | EUROASPIRE I-III are cross-sectional studies conducted inacute hospital in 8 Europeancountries (Republic, Finland,France, Germany, Hungary, Italy,the Netherlands, and Slovenia) toidentify prevalence ofcardiovascular risk factors.Interviews were conducted in1995-96, 1999-2000 and 2006-07.Large variation by country wasobserved. Euroaspire studies arehospital based convenient samples |
| Dugravot, A23 | 2010 | 45-65 y/o | Longitudinal | WHO cut-points | Obesity rates for men were3.4% and 7.7% for managersand unskilled workersrespectively at age 45 and 9.5%and 18.1% for managers andunskilled workers respectively atage 65. Statistically significantincreases in BMI trajectories in20 year period for men andwomen by education andoccupation category. | Europe | Examined socioeconomicdifferences in trajectories of BMIand obesity between age 45 and65 in France. |
| Hubbard, RE24 | 2010 | ≥ 65 y/o | Cross Sectional study usingwave 2 (2004) of the ELSAstudy | WHO cut-points | Mean BMI for the sample was27.5 (95% CI 27.4-27.7).Prevalence of obesity was29.1% for women and 23.4% inmen. | Europe | Analyzed the relationship betweenBMI and frailty and examineddifferences by Frailty definitionused. |
| Gomez-Cabello, A27 | 2011 | ≥ 65 y/o | Longitudinal Study in Spain | WHO cut-points | Prevalence of obesity was40.9% for women and 26.6% formen, the overall rate was 37.6% | Europe | Differences reported using waistcircumference, BMI and body fat. |
| Banks, J99 | 2006 | 55-64 y/o | Cross sectional data fromtwo studies: 2002 HRS inthe US and 2002 ELSA inthe UK | WHO cut-points | Prevalence is 23.0% for the UKand 31.1% for the US. | Comparisonbetweenregions - USA+ Europe | Significant difference at the .01level, controlling for income andeducation |
| Michaud, PC28 | 2007 | ≥ 50 y/o | Cross sectional datacomparing data from theHRS (2004) and the firstwave of SHARE (2004) | WHO cut-points | Obesity was present in 30.7% ofmen in the USA and 17.6% inEurope and 37.9% of women inUSA and 24.2% of women inEurope. The prevalence ofobesity by European country formen was: 19.8% in Austria,18.6% in Germany, 15.8% inSweden, 15.3% in theNetherlands, 20.8% in Spain,15.6% in Italy, 16.2% in France,17.5% in Denmark and 19.2% inGreece. The prevalence ofobesity by European country forwomen was: 26.9% in Austria,22.9% in Germany, 21.5% inSweden, 23.2% in theNetherlands, 33.6% in Spain,23.4% in Italy, 20.3% in France,18.2% in Sweden and 31.2% inGreece. | Comparisonbetweenregions - USA+ Europe | BMI is corrected for self-report biasusing formula derived fromNHANES study (Cawley &Burkhauser, 2006) |
| Avendano,M100 | 2009 | 50-74 y/o | Cross sectional data in 2004comparing three studies:HRS in USA, ELSA inEngland and SHARE inEurope | WHO cut-points | Prevalence of obesity: 28.8% inUS, 26.1% in UK and 17.8% inEurope | Comparisonbetweenregions - USA+ Europe | |
| Young, TK29 | 2007 | ≥ 18 y/o | Cross sectional study using4 studies of Inuit people (1in Alaska, 2 in Canada and1 in Greenland) conductedbetween 1990 and 2001 | WHO cut-points | A total of 15.8% of Inuit menhad obesity while 25.5% ofwomen had obesity. | Multi-countrystudy of Inuitpeople | No significant differences betweencountries were observed |
| Stewart, ST3 | 2009 | ≥ 18 y/o | Uses cross sectional data toestimate trends in Obesityand estimate impact onmortality in 2020 | WHO cut-points | 25.2 [1973-1979]; 26.5 [1990];27.9 [2000]; 28.3 [2005] | North America | Forecasts of life expectancy in theUnited States for a representative18-year old assuming trends insmoking and BMI remain constant.Project 45% of US population willbe obese by 2020. NHANES |
In the United States, studies using data from the National Health and Nutrition Examination Survey (NHANES) report increasing trends in obesity over time 5-10. Ford and colleagues reported an increase in the prevalence of obesity from 11.1% in the 1970’s to 19.3% in the early 2000’s 9. The most recent data from NHANES report obesity prevalence to be approximately 32% for men and 36% for women 8;10. The difference between men and women is not statistically significant based on the overlapping confidence intervals. Nevertheless, the trend over time has continued to increase for men, while for women it seems to be stabilizing 8;11. Race /ethnic differences are also reported in the increasing obesity trends, with African-Americans having the highest rates, followed by Hispanics 8.
Obesity in Canada is lower. The overall prevalence of obesity in the mid 1990’s was reported at 12.8% 12, half that reported in the USA using data from the NHANES study in a similar time period (Table 1). A steady rise in the obesity trends is observed in Canada as well, with obesity rates of 8.1% for men in the 1970’s increasing to 13.4% in the 1990’s and rates of 12.7% rising to 15.4% in women 13. MacDonald and colleagues, using the cut-off point of 27 kg/m2 for obesity, found obesity rate of 35% for men 27% for women in ten provinces from Canada 14. The lower cut-off point explains the large difference in the prevalence between this and the other Canadian studies (Table 1). Nevertheless, we cannot determine why the prevalence rate is higher in men than in women, in contrast to studies in North America. Ethnic differences are also observed in Canada, with Aboriginals reporting higher rates of obesity 15;16.
The few studies available on prevalence of obesity in Latin America and the Caribbean in older adults also report an increase over time. A large variation between countries is also observed 17-19. Using data from the Health, Well-being and Ageing Survey (SABE), the prevalence of category I obesity (BMI of 30 to < 35 Kg/m2) for men and women combined, ranged between 10.4% in Havana to 22.9% in Santiago; the prevalence of category II and extreme obesity (BMI = 35 Kg/m2) ranged from 2.9% in Havana to 15.7% in Montevideo 17. Thus, obesity of any category ranged between 13.3% and 38.6% in the SABE study (Table 1). The two remaining studies summarized in Table 1 on Latin America, were conducted only in Brazil and Mexico. In Brazil the prevalence of obesity seemed to reach a plateau in the early 2000’s for women,while for men the trend continued to increase 18. The prevalence reported in the single country studies falls in the range reported in the SABE study (Table 1).
In Europe, both cross-sectional and longitudinal studies report a large variation in the prevalence of obesity between countries. Using data from the Europe Action on Secondary and Primary Intervention through Intervention to Reduce Events (EUROASPIRE) surveys, the average prevalence of obesity increased from 25% in EUROASPIRE I to 38% in EUROASPIRE III 20. Studies using data from the Survey of Health, Ageing and Retirement in Europe (SHARE) and the English Longitudinal Study of Ageing (ELSA) reported average prevalence of obesity for men of 16.2% and 17.8% for women 21. Nevertheless the variation observed ranges between 12.8% for men in Sweden to 20.2% for men in Spain, and between 12.3% for women in Switzerland to 21.9% for women in Greece (Table 1). Studies using data from only one country also reported a difference in the prevalence of obesity between men and women and an increasing trend in the prevalence of obesity over time 22-27. In most countries the prevalence of obesity is higher for women (Table 1).
Cross-sectional studies comparing USA to Europe showed that obesity rates in USA were higher for both men and women(Table 1). In 2004, the prevalence of obesity for the USA was reported at 30.7% for men compared to 17.6% in Europe, and 37.9% in women compared to 24.2% respectively 28. A large variability is noted again between obesity rates in the different European countries. However, no country reaches the exceedingly high obesity rates of the USA. One last study examined obesity rates among Inuit people in Canada, Alaska and Greenland and reported no significant differences between countries, with an overall prevalence of obesity of 15.8% for Inuit men and 25.5% for Inuit women 29.
Finally, Stewart and colleagues used data from the NHANES to predict obesity rates in 2020 and estimate its impact on mortality 3. Their projections showed that life expectancy is decreased by almost 1 year in the USA for a representative 18 year-old person, assuming trends in smoking continue to decrease and trends in body mass index (BMI) continue to increase at the same rate observed between 1973 and 2005. Additionally, the projection shows that the overall prevalence of obesity for adults in the USA will be 45% by the year 2020 3.
We did not include Asia or Australia as regions in Table 1 because of the limited number of studies available on the epidemiology of obesity in older adults in these continents. Additionally, a large variability in the prevalence of obesity has been reported in the literature on Asian older adults. However, to include all major regions in the world we analyzed two documents that analyze obesity in Asia and Australia. Based on a report by the WHO, the major difficulty with accurately examining obesity among Asians is the large variation in cultural and economic conditions of Asian populations and the fact that current WHO cut-off points for obesity seem to provide an erroneous estimate based on higher prevalence of adverse events at lower BMI values. This report by the WHO proposes that the cut-off point for obesity among Asian adults should be 25 kg/m2 30.
The WHO report on Asia summarizes some studies that have looked at epidemiology of obesity. Most data on obesity in Asia come from single country studies or from countries where a large portion of the population is of Asian origin, like the island of Mauritius. Obesity trends are rapidly rising in all Asian nations. Obesity rates range between less than 1% in rural populations in countries like China, to around 9% in urban areas of Malaysia. A large variation by gender and ethnicity is observed in several countries including Malaysia and China. In summary, the data from Asian countries reports much lower obesity rates compared to other regions. The WHO however, strongly advocates for a new definition of obesity with different cut-off points based on the trends in obesity rates and the increase in the prevalence of obesity associated complications such as cardiovascular diseases.
In Australia, analysis of trends from cross-sectional surveys conducted since the 1980’s were summarized by the Australian Institute of Health and Welfare in a bulletin published in 2004 31. Similar to what has been reported in other continents, the rates of obesity among older adults has increased over time. Between the 1980’s and the early 2000’s an increase in prevalence of obesity was observed from 11% to 23% in adults over 65 31. The most recent reports show that between 25-30% of adults approaching retirement in Australia are obese.
In summary, obesity has increased noticeably in all continents among older adults. Large variations between countries, race/ethnic groups and genders are observed. Despite these variations, public health implications need to be carefully analyzed and addressed to prevent disability and decreased quality of life for older adults around the world in the near future.
Obesity and Disability
Disability is a broad term that can be defined in many different ways. Lack of a single definition and availability of several validated tools to measure different types of disability make cross-study comparisons on disability difficult. Nevertheless, the ample literature showing that disability increases the risk of mortality and institutionalization and affects quality of life in older age make disability a concept that must be carefully analyzed and better understood 32-35. Conditions that increase the risk of disability are therefore highly important.
Table 2 summarizes relevant studies that analyze the relationship between obesity and disability. Obesity is not measured consistently although all studies use either BMI, waist circumference or body composition to define obesity. Similarly, the definition of disability varies between the different studies. The first studies listed are longitudinal studies. They are consistent in showing that, over time, the presence of obesity increases the risk of becoming disabled 25;36-43. Nevertheless, of the nine longitudinal studies listed, seven studies use Activities of Daily Living (ADL) to define disability 25;36;38;39;41-43. Five of the seven studies use the same six activities (walking across a room, bathing, eating, dressing, toileting and transferring in and out of bed) and define disability as difficulty performing one or more activities 25;36;38;39;43. From these studies we can conclude that obesity is an independent risk factor for developing ADL disability over time. The remaining studies use upper and lower body function and work related disability. Each study concludes that obesity increases the risk of the defined disability 37;40. The studies by Reynolds et al. and Walter et al. also conclude that obesity hampers the probability of recovery from disability in older adults 38;41. In some of the longitudinal studies, the effect of obesity on disability was larger for women compared to men (Table 2).
Table 2.
Summary of literature review of studies analyzing the relationship between obesity and disability
| Author | Year | Age ofparticipants | Type ofStudy | Obesitymeasure used | Disability measure used | Relationship between obesityand disability | Notes |
|---|---|---|---|---|---|---|---|
| Ferraro,KF37 | 2002 | 25-74 y/o | Longitudinalstudy | BMI with WHOcut-off points | A total of 19 items from the StanfordHealth Assessment QuestionnaireDisability Index. Nine items weregrouped to measure lower-bodydisability and ten items were grouped tomeasure upper-body disability. | At baseline, obesity was related toupper-body disability but not lowerbodydisability. Overtime, bothunderweight and obesity wererelated to upper and lower-bodydisability. | Relationship betweenoverweight and disabilitywas not consistent for thedifferent groupsanalyzed. |
| Visscher,TL40 | 2004 | Adults 20-92y/o,dichotomizedusing 65 ascut-off point | Longitudinalstudy | BMI with WHOcut-off points | Receiving any work disability pensionfrom the National Social InsuranceInstitutions in Finland | Overweight and obesity wererelated to higher risk of workdisability. | Risk of work disabilitywas higher for youngeradults (<65 y/o)compared to older adults(>65 y/o). Effect ofobesity on onset ofcardiovascular disease,long-term medication useand unhealthy life yearswas also assessed. |
| Sturm, R39 | 2004 | 50-69 y/o | Longitudinalstudy | BMI with WHOcut-off points | Difficulty with ADL or positive reports of“impairment or health problem thatlimits the kind/amount of paid work.” | The probability of ADL disabilitywas 50% higher for men with BMIbetween 30-35, compared to menwith BMI between 20-25. Theprobability increased to 300% ifBMI was > 35. For women theeffect is larger with double the riskfor women with BMI between 30-35 and four times the risk forwomen with BMI >35. | Uses HRS study |
| Reynolds,SL38 | 2005 | ≥ 70 y/o | Longitudinalstudy | BMI using WHOcut-off point of 30to create 2categories(Obese vs. Non-obese) | Difficulty in one or more ADL | Incidence of disability between1993 and 1998 was higher forobese adults compared to non-obese adults (16.7% vs. 12.7%).Obese older adults also hadsignificantly higher probability ofbecoming disabled compared tonon-obese adults. | Obesity had little effecton life expectancy.Obesity also affectedlikelihood of recoveringfrom disability. |
| Wilkins,M42 | 2005 | ≥ 45 y/o | Conductscrosssectionalanalysisusing datafrom CCHSin 2003 andlongitudinalanalysisusing datafrom theNPHSwaves 1-4 | BMI with WHOcut-off points | ADL/IADL | Dependency in ADL/IADL wasalmost the same for older adultwho were underweight and thosewith obesity class III. | Controlling forconfounders in stepwisefor at the end of analysis.Obesity was predictive ofdependency in ADL/IADLover time. |
| Al Snih,S36 | 2007 | ≥ 65 y/o | Longitudinalstudy | BMI with WHOcut-off points | Difficulty with one or more ADL | A “U” shaped relationship betweenBMI and disability was observed.Disability-free life expectancy washighest for older adults with BMIbetween 25-30. | Used sample with non-Hispanic Whites, African-Americans andHispanics. |
| Lang, IA25 | 2008 | ≥ 65 y/o | Longitudinalstudy | BMI with WHOcut-off points | Self-reported and measured physicalfunction was assessed. Self-reportedphysical function was assessed throughdifficulty in one or more ADL. Measuredphysical function was assessed throughthe SPPB, a score ≤ 7 was considereddisability. | Rise in poor self-reported andmeasured physical function withincreasing BMI. Over time obesewere more likely to developdisability compared to normal-weight adults. | Uses ELSA study |
| Walter, S41 | 2009 | ≥ 55 y/o | Longitudinalstudy | BMI with WHOcut-off points andWC divided inthree categoriesfor men andwomenseparately. | ADL from the HAQ-DI Index. HAQ-DIscore ≥ 0.5 considered disability | Obesity doubles the risk ofdisability over time. | BMI also decreases theprobability of recoveryfrom disability over time. |
| Al Snih S44 | 2010 | ≥ 65 y/o | Crosssectionalstudy usingdata fromthe SABEstudy thatincluded 6cities inLatinAmerica | WHO cut-points,separatescategory I (BMIbetween 30 and34.9) fromcategory II andextreme obesity(BMI ≥ 35) | Difficulty in one or more ADL | Obesity is an independent factorcontributing to ADL disability.Category I and Category II obesityare presented separately. | Variation by countryobserved, howeverrelationship present in allcountries. |
| Himes,CL49 | 2000 | ≥ 70 y/o | Cross-sectionalstudy | BMI with WHOcut-off points | Self-reported limitations in one or moreADL or any difficulty with one or moreitems of the Nagi disability scale. | As BMI increase ADL limitationsincrease | Effect of obesity on eachADL was analyzed andon ADL and Nagiactivities separately.Effect of obesity on fivemedical conditions is alsoanalyzed. |
| Pedersen,AN51 | 2002 | 80 y/o | Cross-sectionalstudy | BMI with 3categories: <24kg/m2, 24-29kg/m2, > 29kg/m2 and bodyfat mass and fat-free massmeasured withbioelectricalimpedance. | Measured with muscle strength, physicalactivity, functional ability and selfreportedfunctional ability. | Higher body weight and higherBMI were correlated with bettermuscle strength. Individuals withBMI < 24 had a tendency of havinghigher muscle strength comparedto individuals with BMI > 24,differences were only statisticallysignificant for women. There wasno difference in physical activity orfunctional ability by BMI group. | |
| Chen, H47 | 2002 | 65-92 y/o | Cross-sectionalstudy | Waistcircumferencedivided inquintiles for menand womenseparately orBMI with WHOcut-off points | A 12 item ADL questionnaire adaptedfrom Katz scale. Score divided in threecategories: 1) no disability, 2) somedisability and 3) considerable disability | Weight change after age 50 had a“U” shaped relationship withdisability. Abdominal obesity andweight gain were associated withgreater disability in men andwomen. BMI greater than 35 wasassociated with greater disabilityonly among women. | Representative sample ofHispanics inMassachusetts. Womenhad a higher disabilityscore compared to men.Higher proportion ofwomen compared to menhad obesity. However,men had a higheraverage waistcircumference comparedto women. Womenreported higher averageweight change comparedto men. |
| Zoico, E50 | 2004 | Women 67-78 y/o | Crosssectionalstudy | BMI with WHOcut-off points andfat percentagemeasured withDXA | Combination of 3 scales: ADL, threeRosow and Breslau functional items andIADL | Both higher BMI values and higherfat percentage were associatedwith higher prevalence of disability | |
| Woo, J54 | 2007 | ≥ 65 y/o | Cross-sectionalstudy | BMI using cut-offpoint previouslyreported forAsianpopulations | Physical activity level determinedthrough the PASE scale or difficultyperforming one of the following: walking2-3 blocks, climbing 10 steps, mealpreparation, doing heavy house workand shopping. | Older adults with category I andcategory II obesity (BMI between25-29.9 kg/m2 and ≥ 30 kg/m2) hadgreater number of impairmentsperforming the different activities.A “U” shape relationship betweenBMI and physical performance isreported. | Study using men andwomen in Hong-Kong.Additional analyses showthat fat mass associatedwith physical functionwhile apendicular musclemass was not. |
| Alley, DE45 | 2008 | ≥ 60 y/o | Cross-sectionalstudy usingdata toanalyzedisabilitytrends inthe UnitedStates | BMI with WHOcut-off points | Two types of disability indicators: 1)functional limitations 2) ADL | At baseline, prevalence offunctional impairment was lowestamong the normal weight adults(26.7%) and increased foroverweight adults (27.4%) andobese adults (36.8%); prevalenceof ADL impairment was 5% forunderweight, 4.3% for overweightand 6% for obese older adults. Atfollow up, the prevalence offunctional impairment was 26.6%for normal weight adults, 25.8% foroverweight and 42.2% for obeseolder adults; prevalence of ADLimpairment was 3.5% in normalweight, 3% in overweight and 5.5%in obese. | “J” shaped observed inthe relationship betweenobesity and disabilityreported in other studies,for ADL disability atbaseline and follow-upand for functionalimpairment at follow-up.Over time the prevalenceof functional impairmentincreased for obeseindividuals, but nochange was observed forADL impairment. |
| Chen, H48 | 2008 | ≥ 60 y/o | Cross-sectionalstudy | Sex specificquartiles andWHO cut-offpoints in additionto waistcircumference | A total of 19 questions to assess thelevel of difficulty in performing physicalor mental task without using specialequipment were used to measurefunctional status. The items wereclassified into five domains: 1) ADL, 2)IADL, 3) Leisure and social activities, 4)Lower extremity mobility, 5) generalphysical activities. Disability was definedas with one or more activities within agiven domain. | BMI was positively associated withall measures of functional disabilityin women and with disability in alldomains but ADL and IADL inmen. | Waist circumference alsoassociated to disability.Waist circumference issuggested as a strongerindicator of disability forwomen compared tomen. |
| Rolland,Y52 | 2009 | Women 75y/o or older | Cross-sectionalstudy | Percentage bodyfat above the60th percentilemeasured withDXA | Difficulty in 3 or more mobility activities(walking, climbing stairs, going downstairs, rising from chair or bed, pickingup object from floor, lifting heavy objector reaching for objects). | Compared with the group withnormal body composition, obesewomen had 44-79% higher odds ofhaving difficulty with functionalmeasures. | Association betweenobesity, sarcopenia andtheir combination withdisability was examined.Obesity alone andsarcopenia with obesityboth increase the risk ofdisability. |
| Berraho,M46 | 2010 | ≥ 65 y/o | Cross-sectionalstudy | BMI with WHOcut-off points | Hierarchical index aggregating threedomains of disability into a singlemeasure: mobility, ADL and IADL.Individuals were considered dependentif they could not perform at least oneactivity of the domain without help. | The highest proportion ofindependent older adults wasamong those with a BMI rangebetween 25-30 kg/m2. The highestrates of mobility disability wereobserved in obese older adults. | Differences observed inthe relationship betweenobesity and disabilitydepending on type ofdisability measured. |
| Vincent,HK53 | 2010 | ≥ 60 y/o | LiteratureReviewarticle withcross-sectionalandlongitudinalstudies | BMI, body fatpercentage or fatmass. | Mobility disability measure with at leastone of the following: walk time, walkdistance, transfers, chair rise to timedup-and-go test to stair climb. | Cross-sectional studies show thatobesity is associated with poorlower extremity mobility in oldermen and women. Most longitudinalstudies reported that higheradiposity was related to decliningmobility over time. Walking, stairclimbing, and chair rise wereespecially affected if BMI wasgreater than 35 kg/m2. Mobilityimpairment in older obese adultswas more common for womencompared to men. | A few interventionalstudies reviewed provideevidence that weight lossis related with bettermobility. |
| Wee CC43 | 2011 | ≥65 y/o | LongitudinalStudy | BMI with WHOcut-off points | Difficulty with one or more ADL orDifficulty with one or more IADL | Overweight and obesity wereassociated with new or progressiveADL and IADL disability in a dose-dependent manner, particularly forwhite men and women. | Obesity was notassociated with mortality,except for those with atleast moderately severeobesity. |
Following the longitudinal studies, cross-sectional studies analyzing the relationship between obesity and disability are listed (Table 2). Similar to the longitudinal studies, disability is defined in different ways. Of the 11 cross-sectional studies included, seven use ADL exclusively or in combination with other functionality measures to define disability 44-50. Three studies also use Instrumental Activities of Daily Living (IADL) to define disability 46;48;50. The remaining studies use either physical function or mobility disability to define disability 51-54. All studies conclude that obesity is related to increased disability regardless of how it is measured. Some of the studies analyze the relationship between obesity and muscle strength and suggest that, despite the deleterious effects of obesity on muscle function, additional pathways need to be analyzed to understand the pathophysiology behind the onset of disability in older obese adults 50-54.
Several studies report that the relationship between weight or BMI and disability has a “U” or a “J” shape, meaning that not only obesity but underweight older adults have increased risk of disability 36;45;48. Normal weight and maybe some overweight older adults seem to have the lowest risk of disability of all weight or BMI groups. This has important implications for prevention and treatment schemes, since losing too much weight can be detrimental for older adults as well.
In summary, obesity is related to increased risk of disability among older adult populations. Obesity also seems to affect recovery from disability over time. Obesity not only affects functional status but it also affects mobility. Policy makers and healthcare providers need to keep this relationship in mind, and design obesity prevention and obesity management programmes that can improve functional status in older adults and protect them from becoming disabled, with resultant poor quality of life.
Implications of obesity on chronic diseases
Despite the widely know deleterious effects of obesity on overall health, obesity in older age has to be analyzed with caution. Obesity significantly increases the risk of death among older adults. Never the less, the relationship between BMI and mortality is unique in the older adult population because very low BMI values are related to the highest mortality risk, this risk decreases as BMI increases to normal and overweight values and then mortality risk increases again, with a sharp increase in BMI values greater than 35kg/m2 36;55;56. Additionally, weight loss has been reported as a risk factor for adverse events in some older adults including fractures, falls and mortality 57;58. Despite this, healthcare costs for older obese adults are higher than for older adults with normal weight59;60. Similarly, disability rates and complications from obesity have been widely reported among the older adult population 61-63. We reviewed the literature and have summarized the implications of obesity on different diseases in the older adult population.
Obesity and Cardiovascular disease
Obesity is an independent risk factor for development of heart failure, acute events like myocardial infarctions and stroke in older adults 64;65. Obesity increases the risk of hypertension and affects overall response to anti-hypertensive medications 66-68. A “U” shaped relationship between BMI and hypertension has been reported 69. Two major causes have emerged as explanatory causes for cardiovascular disease resulting from obesity: anatomic and physiologic alterations. Anatomic alterations are explained because obesity affects the architecture and physiology of the cardiovascular system. Obesity causes atrial and ventricular enlargement and plaque formation in the vessels 70-72. These changes not only affect cardiovascular function, but also increase the risk of developing potentially lethal conditions like atrial fibrillation and abdominal aortic aneurysms 73;74.
Obesity triggers metabolic dysregulation and inflammation 50;75;76. Decreased levels of natriuretic peptide, a peptide that protects against acute events like myocardial infarctions, have been reported 68;77. Other physiologic alterations include increased levels of inflammatory markers (interleukin-6, C - reactive protein and tumor necrosis factor) that affect the body’s response to physiologic changes and put an additional burden on the cardiovascular system 76. Increased adiposity enhances insulin resistance and therefore the risk for adverse cardiovascular events overall 50;78.
Obesity, Diabetes and the Metabolic Syndrome
Obesity, diabetes and the metabolic syndrome are closely related. Obesity and diabetes are distinct clinical conditions that occur independently despite sharing some pathophysiologic pathways. The metabolic syndrome is also independent from obesity and diabetes. It is a collection of risk factors that cause damage to the cardiovascular system, increasing the risk of heart attack, stroke and other cardiovascular diseases. Increased body fat and increased blood sugar are two of the eight components of the metabolic syndrome79;80.
Unlike the relationship between obesity and mortality in older adults, the relationship between obesity, diabetes and the metabolic syndrome is very similar in older adults compared to younger adults. A large body of evidence has shown that obesity increases the risk of developing diabetes and the metabolic syndrome 80;81. There is also evidence that obesity, diabetes and the metabolic syndrome are independent risk factors for cardiovascular disease 80. Increased oxidative stress in fatty tissue of obese individuals has been proposed as a pathogenic mechanism leading to the metabolic syndrome 82. Additionally, severity of obesity (determined by National Heart Lung and Blood Institute Task Force categories: class 1, class 2 and class 3) is associated with an increasing trend in risk of development of diabetes and the metabolic syndrome 83. It has been reported that this relationship between obesity, diabetes and the metabolic syndrome is especially important among minority populations in developed countries given the higher rates of obesity compared to other population groups and the higher rates of complications and mortality 79.
Obesity and Cancer
More than 60% of cancers occur over the age of 65 84. In the last decade, findings in cancer epidemiology have highlighted the importance of the relation between obesity and cancer 85. Increased body mass and adiposity have been established as risk factors for the development of cancers that affect a large portion of the older adult population such as colon cancer, breast cancer, and prostate cancer 85. Three hormonal systems have been proposed as causal pathways : insulin and insulin-like growth factor axis, sex steroids and adipokines 85;86. These hormonal systems are altered in obesity; however, their role in the development of cancer is probably different for each cancer site. Additionally, the link between obesity and cancer seem to be different for men and women 85-87.
To date there have been no clinical trials exploring the effect of losing weight, or even maintaining weight, on cancer incidence 85;86. However, there is evidence from observational studies that weight maintenance and controlled weight loss may decrease the risk of developing some types of cancers 88;89. Despite the limited information, it has been shown that obesity increases the risk of delayed cancer diagnosis, complications during cancer treatment and poor outcomes after treatment 90;91.
Obesity and arthritis
A common limitation when addressing arthritis in older adults is the lack of differentiation between the types of arthritis described. The most common types of arthritis affecting older adults are osteoarthritis, rheumatoid arthritis and gout. The pathophysiology, treatment and course of each type of arthritis are very different. However, the negative effect of arthritis on older adults is mostly due to its effect on overall physical and mental health and disability rather than a direct increase in mortality risk 92.
The relationship between obesity and arthritis has not been completely explained. Despite the differences in the most common types of arthritis in older adults, both obesity and arthritis are pro-inflammatory conditions that increases the concentration of cytokines and adipokines as previously reported 93. Additionally, arthritis impairs physical activity, necessary for weight loss, and a cornerstone for self-management of arthritis because it diminishes pain and improves physical function 92;94. Both increased levels of inflammatory markers and decreased physical activity in relation to obesity impede adequate management of arthritis and increase the long term effects of the disease 95. In addition, obesity accelerates the deterioration of joint function in older adults with arthritis and negatively affects some outcomes from surgical interventions 92;95.
Obesity and some Geriatric syndromes
Obesity has been linked to some geriatric syndromes. The pro-inflammatory state caused by obesity has been linked to age related muscle loss or sarcopenia 4;50. Sarcopenia has been shown to increase disability and overall mortality and may explain some of the complications reported in obese older adults 4. Sarcopenia and obesity are independent conditions with separate pathophysiologic pathways. However, older adults with comorbid sarcopenia and obesity have become the centre of several studies. Co-occurrence of sarcopenia and obesity places older adults in a unique state of disease that increases the risk of adverse events and requires special interventions 4;50;52;54. Additionally, the pro-inflammatory state has also been related to vascular dysfunction in the brain that increases the production of beta-amyloid, a key component of senile plaques that accumulate in the brain in Alzheimer’s disease 96-98.
In summary, the pro-inflammatory state caused by obesity, in addition to the limitations in physical function, are common links to the added burden of disease when obesity is present concomitantly with many chronic conditions in older adults. Additionally, obesity is a marker of poor outcomes for most interventions for chronic conditions and interferes with management of most chronic diseases in older adults.
Conclusions
Obesity among older adults has increased noticeably in the last two decades in all continents. However, large variations between countries, race/ethnic groups and genders are observed. Obesity is related to increased risk of disability among older adult populations regardless of the measures used. Obesity affects functional status and mobility. Inflammation caused by obesity is linked to the added burden of disease when obesity is present concomitantly with many chronic conditions in older adults. Additionally, it is a marker of poor outcomes for most interventions for chronic conditions and interferes with management of most chronic diseases in older adults.
Policy makers and healthcare providers need to keep obesity-related health outcomes in mind and design obesity prevention and management programmes that can improve functional status in older adults and protect them from becoming disabled with resultant poor quality of life.
Acknowledgment
This study was supported by grants R03-AG029959, R01-AG017638, and R01-AG010939 from the National Institute on Aging, U.S. Dr. Al Snih is supported by a research career development award (K12HD052023: Building Interdisciplinary Research Careers in Women’s Health Program–BIRCWH) from the Eunice Kennedy Shriver National Institute of Child Health & Human Development; the National Institute of Allergy and Infectious Diseases; and the Office of the Director, National Institutes of Health.
Footnotes
Conflict of interest The authors have nothing to disclose.
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