what percent of obese people return to a normal weight
Am J Public Health. 2015 September; 105(9): e54–e59.
Probability of an Obese Person Attaining Normal Body Weight: Accomplice Study Using Electronic Health Records
Alison Fildes, PhD, Judith Charlton, MSc, Caroline Rudisill, PhD, Peter Littlejohns, MD, A. Toby Prevost, PhD, and Martin C. Gulliford, FFPH, MA 
Abstract
Objectives. We examined the probability of an obese person attaining normal torso weight.
Methods. We drew a sample of individuals aged xx years and older from the United Kingdom's Clinical Practice Research Datalink from 2004 to 2014. We analyzed data for 76 704 obese men and 99 791 obese women. Nosotros excluded participants who received bariatric surgery. We estimated the probability of attaining normal weight or five% reduction in body weight.
Results. During a maximum of nine years' follow-upwardly, 1283 men and 2245 women attained normal torso weight. In elementary obesity (body mass index = thirty.0–34.9 kg/chiliad2), the annual probability of attaining normal weight was 1 in 210 for men and ane in 124 for women, increasing to 1 in 1290 for men and 1 in 677 for women with morbid obesity (body mass alphabetize = 40.0–44.9 kg/chiliadtwo). The annual probability of achieving a 5% weight reduction was ane in 8 for men and 1 in seven for women with morbid obesity.
Conclusions. The probability of attaining normal weight or maintaining weight loss is low. Obesity treatment frameworks grounded in customs-based weight management programs may be ineffective.
Overweight and obesity are growing global health concerns.one Strategies to control obesity emphasize obesity management and weight reduction every bit well as obesity prevention. In the United Kingdom, a national strategy report recommends that the direction of obesity be an integral office of clinical practice.two This envisages that patients may transition from obesity to a more than healthy torso weight. A target of five% body weight loss is frequently recommended for obese individuals who intend to lose weight.3 However, access to weight management interventions may be limited,4 and weight management interventions accept just pocket-size and poorly maintained furnishings on trunk weight.5,6 To understand the frequency with which reductions in body mass alphabetize (BMI, defined as weight in kilograms divided past the square of superlative in meters) may occur in a large population, nosotros estimated the probability of an obese individual attaining normal body weight or a reduction of v% in body weight.
METHODS
We conducted a population-based cohort study using main care electronic wellness records from family practices in the United Kingdom. We selected a cohort of adults aged twenty years and older from the UK Clinical Practice Research Datalink (CPRD), an anonymized database of longitudinal patient electronic medical records from main care. The CPRD is the world's largest principal intendance database and contains more than than 7% of the UK population, with nearly 700 general practices contributing data that meets quality standards for research.vii The CPRD data are considered to exist broadly representative of the United kingdom population in terms of patient demographic characteristics and the size and distribution of practices.vii Our research was part of a larger report to evaluate the utilise of bariatric surgery. Nosotros aimed to estimate trunk weight transitions in the absence of bariatric surgery; therefore, we excluded participants who received bariatric surgery.
Sample Selection
There were two 006 296 patients registered in the CPRD between November 1, 2004, and Oct 31, 2014, who were aged 20 years or older and had three or more than BMI records. A minimum of 3 BMI records per patient was required to gauge weight changes, including weight regain following weight loss. The annual count of the CPRD registered population aged 20 years and older peaked at 3.7 million during this menstruum, with a full of seven.1 million participants aged 20 years or older registered at any time during the menstruum.
We classified participants according to the BMI value of their first tape into 6 categories: eighteen.five to 24.9 (normal weight), 25.0 to 29.9 (overweight), 30.0 to 34.9 (unproblematic obesity), 35.0 to 35.9 (severe obesity), 40.0 to 44.9 (morbid obesity), and 45.0 or greater (superobesity) kilograms per meters squared. We selected a random sample of upwardly to thirty 000 participants, using the sample command in Stata version thirteen (StataCorp LP, College Station, TX), from each category of BMI and gender, resulting in 314 477 participants. There were fewer than xxx 000 women with a BMI of 45 or greater kilograms per meters squared and fewer than 30 000 men with a BMI of either twoscore to 45 or 45 or greater kilograms per meters squared.
We then extracted full CPRD records for this sample. We analyzed data for research quality records for each participant. The start was the latest of November 1, 2004, the participant registration appointment, or the general practice CPRD outset engagement. The end engagement was the primeval of October 31, 2014, the engagement death or end of registration, or the last data collection date for the general practice. We excluded the 2738 (ane%) participants who had bariatric surgery and the 32 757 (x%) participants who had fewer than 3 BMI values recorded betwixt Nov ane, 2004 and October 31, 2014; this left 278 982 participants for further analysis.
Analysis
We conducted a longitudinal analysis of BMI records. The outset date for each participant was the later of November 1, 2004 or the beginning of the patient'southward CPRD record. The finish engagement was the earlier of Oct 31, 2014 or the cease of the patient's CPRD record. Nosotros used the first BMI record later the participant outset engagement as the index BMI, and we used the date of this record as the index appointment. We evaluated the number of BMI records for each BMI category, and nosotros calculated the number of records showing either an increase or a subtract in BMI category. For patients who showed a decrease in BMI category, nosotros evaluated whether subsequent changes in BMI category were increases or further decreases.
Nosotros analyzed data in a time-to-issue framework to evaluate the proportion of patients from each starting BMI category who attained either, first, a normal trunk weight or, second, a 5% reduction in body weight during the 9-year follow-upwards. We did not envisage a v% reduction in body weight in the original study protocol, but nosotros added it as a minor amendment because this is a widely recommended target for torso weight reduction. In the get-go assay, we estimated the almanac probability of attaining normal torso weight. We used the number of events (BMI category recorded as < 25 kg/thousand2) and the person-years of follow-up to judge the almanac rates and their confidence intervals (CIs), which nosotros converted to annual probabilities using the formula 1 – exp–rate.
Amongst participants who reduced their BMI category, we evaluated the management of the next modify in BMI category. In the second analysis, to examine the proportion of participants who lost 5% of their trunk weight, nosotros too evaluated the evolution of a trunk weight that was more than 95% of the initial body weight in a time-to-event framework. We conducted analyses in Stata version 13 using the stset, sts list, and stcox commands.
RESULTS
Our analysis included 278 982 participants—129 194 men and 149 788 women—who were registered betwixt Nov 1, 2004, and Oct 31, 2014, and had three or more BMI measurements recorded during this menstruum. The initial distribution of the sample past gender and BMI is shown in Table 1. The mean age was 55 years for men and 49 years for women. At the index date (date of the first BMI record in the report period) there was a minimum of 25 000 male and 23 000 female participants each for the BMI categories 18.v to 24.9 (normal weight), 25.0 to 29.nine (overweight), 30.0 to 34.ix (simple obesity), and 35.0 to 39.ix (severe obesity) kilograms per meters squared. In that location were similarly high numbers of female participants with an index BMI of 40.0 to 44.9 kilograms per meters squared (morbid obesity) but fewer male participants in this category at baseline (14 767). At that place were 6481 men and 18 451 women with a baseline BMI of 45.0 or greater kilograms per meters squared (superobese).
Table 1—
Number of BMI Records per Participant and Proportions Showing No Change, Increase, Decrease, or Weight Cycling Over 9 Years Following First BMI Record: United Kingdom, 2004–2014
| Initial BMI Category | No. | Age, Years, Hateful ±SD | Number of BMI Records, Median (IQR) | All Records Show No Alter in BMI Category, Frequency (%) | ≥ ane Decrease in BMI Category and No Increases, Frequency (%) | ≥ one Increase in BMI Category and No Decreases, Frequency (%) | Records Show Both Increases and Decreases in BMI Category, Frequency (%) |
| Men, kg/m2 | |||||||
| 18.5–24.9 | 25 082 | 58 ±xviii | 5 (3–seven) | xiv 217 (57) | 799 (3) | 5 032 (20) | v 034 (xx) |
| 25.0–29.9 | 27 408 | 58 ±15 | 5 (iii–8) | 13 281 (48) | three 243 (12) | 3 428 (thirteen) | vii 456 (27) |
| xxx.0–34.9 | 27 966 | 56 ±fourteen | 6 (4–10) | x 320 (37) | four 620 (17) | ii 901 (10) | 10 125 (36) |
| 35.0–39.9 | 27 490 | 53 ±13 | 7 (4–12) | 7 200 (26) | five 070 (18) | two 525 (9) | 12 695 (46) |
| 40.0–44.ix | 14 767 | l ±13 | 8 (iv–xiv) | ii 761 (19) | 2 810 (19) | 1 596 (11) | seven 600 (51) |
| ≥ 45.0 | half dozen 481 | 47 ±13 | 8 (4–14) | 2 828 (44) | 1 353 (21) | NA | 2 300 (35) |
| All | 129 194 | 55 ±xv | 6 (four–10) | 50 607 (39) | 17 895 (14) | 15 482 (12) | 45 210 (35) |
| Women, kg/mtwo | |||||||
| 18.5–24.nine | 23 640 | 46 ±20 | iv (3–7) | xiv 047 (59) | 844 (4) | 4 346 (18) | iv 403 (19) |
| 25.0–29.9 | 26 357 | 52 ±19 | 5 (3–eight) | x 140 (38) | 3 696 (fourteen) | iv 197 (xvi) | 8 324 (32) |
| 30.0–34.9 | 27 251 | 52 ±17 | 6 (iv–x) | eight 275 (30) | iv 621 (17) | 3 626 (13) | 10 729 (39) |
| 35.0–39.9 | 27 373 | 49 ±16 | vii (4–11) | 6 322 (23) | 4 910 (18) | iii 304 (12) | 12 837 (47) |
| forty.0–44.nine | 26 716 | 48 ±fifteen | 7 (iv–13) | 4 680 (xviii) | five 009 (19) | three 108 (12) | 13 919 (52) |
| ≥ 45.0 | 18 451 | 46 ±fourteen | 8 (5–14) | 8 945 (48) | three 472 (19) | NA | 6 034 (33) |
| All | 149 788 | 49 ±17 | 6 (4–10) | 52 409 (35) | 22 552 (xv) | xviii 581 (12) | 56 246 (38) |
Table i also shows the frequency and proportion of participants recorded as having no change in BMI category, increases in BMI category, decreases in BMI category, or weight cycling (both increases and decreases) over 9 years following first BMI record. The number of BMI records per participant increased with baseline BMI category. The proportion of participants showing no change was greatest among participants in the normal weight category (men: 57%; women: 59%) and decreased with higher baseline BMI, with the exception of those initially categorized every bit superobese. Only 14% of men and xv% of women showed decreases in BMI category without increases over the same menses.
The proportion of participants with records indicating only decreases in BMI increased with baseline BMI category, which were the highest proportions observed for those initially categorized every bit morbidly obese (men: xix%; women: 19%) and superobese (men: 21%; women: 19%). A small proportion of participants (men: 12%; women: 12%) had only BMI category increases recorded, with the highest proportion found among those initially categorized as normal weight (men: 20%; women: 18%). Weight cycling was observed in more than a third of participants (men: 35%; women: 38%) and was most common among severely obese (men: 46%; women: 47%) and morbidly obese (men: 51%; women: 52%) participants.
Table 2 shows the frequency of transitioning to normal trunk weight during upward to 9.9 years follow-up subsequently the first BMI record. During a maximum of 9 years' follow-upward, 1283 men and 2245 women attained normal body weight records. The almanac probability of achieving normal body weight was i in 210 for men and 1 in 124 for women with elementary obesity. The probability declined with increasing BMI category. In morbidly obese patients, the annual probability of achieving normal weight was i in 1290 for men and 1 in 677 for women. In women, the probability of achieving normal weight among superobese participants was 1 in 608, which is like to that observed among morbidly obesite participants. In the smaller number of superobese men, the probability was higher at i in 362.
Tabular array two—
Annual Probability of Achieving Normal Weight by Initial BMI Category and Gender: Britain, 2004–2014
| Initial BMI Category | No. Participants | No. Person-Years During Follow-Up | No. Attaining Normal BMI | Annual Probability of Attaining Normal BMI, Estimate (95% CI) |
| Men, kg/mii | ||||
| thirty.0–34.9 | 27 966 | 179 746 | 857 | ane in 210 (197, 225) |
| 35.0–39.9 | 27 490 | 174 386 | 249 | 1 in 701 (619, 797) |
| twoscore.0–44.9 | 14 767 | 91 528 | 71 | ane in 1 290 (1023, 1651) |
| ≥ 45.0 | 6481 | 38 367 | 106 | ane in 362 (300, 442) |
| Women, kg/m2 | ||||
| 30.0–34.9 | 27 251 | 173 066 | 1 398 | 1 in 124 (118, 131) |
| 35.0–39.9 | 27 373 | 175 356 | 408 | 1 in 430 (390, 475) |
| 40.0–44.9 | 26 716 | 170 483 | 252 | 1 in 677 (599, 769) |
| ≥ 45.0 | 18 451 | 113 540 | 187 | 1 in 608 (527, 704) |
Annual probabilities of achieving a clinically relevant 5% reduction in body weight are shown in Table iii. The annual probability of experiencing a 5% weight reduction was 1 in 12 for men and 1 in x for women with simple obesity. Probability increased with increasing BMI category. For morbidly obese patients, the annual probability of achieving 5% reduction in body weight was 1 in 8 for men and ane in 7 for women. The highest annual probability was observed among superobese patients (1 in 5 for men and one in 6 for women). All the same, amidst participants who lost 5% body weight, 52.7% (95% CI = 52.4%, 53.0%) at 2 years and 78.0% (95% CI = 77.7%, 78.3%) at 5 years had BMI records that indicated weight proceeds to values above the 5% weight loss threshold.
TABLE iii—
Annual Probability of Achieving a 5% Reduction in Body Weight by Initial BMI Category and Gender: United Kingdom, 2004–2014
| Initial BMI Category | No. Participants | No. Person-Years During Follow-Upwardly | No. Attaining 5% Reduction in Body Weight | Annual Probability of Attaining 5% Reduction in Body Weight |
| Men, kg/10002 | ||||
| 30.0–34.9 | 27 966 | 135 394 | 11 869 | ane in 12 |
| 35.0–39.ix | 27 490 | 118 266 | thirteen 805 | one in 9 |
| forty.0–44.9 | 14 767 | 57 099 | eight 100 | 1 in 8 |
| ≥ 45.0 | 6 481 | xx 900 | 4 177 | 1 in 5 |
| Women, kg/m2 | ||||
| 30.0–34.9 | 27 251 | 123 567 | 12 792 | 1 in 10 |
| 35.0–39.9 | 27 373 | 116 042 | 13 972 | 1 in ix |
| twoscore.0–44.nine | 26 716 | 103 849 | 15 208 | ane in seven |
| ≥ 45.0 | 18 451 | 63 397 | 11 340 | 1 in half dozen |
Figure ane shows the percentage of men and women whose later BMI records revealed an increase, a further decrease, or no change in BMI category amidst patients with a recorded decrease in BMI category over the written report menstruation. The majority of patients (men: 61%; women: 59%) whose records showed a subtract in BMI category went on to tape a subsequent increase in BMI category. These proportions were similar for men and women and across BMI categories. The proportion of patients who showed a second decrease in BMI category was highest among the morbidly obese (men: 16%; women: 19%) and superobese (men: 23%; women: 24%), and was considerably less frequent in lower BMI categories. Overweight patients and those with elementary obesity were the most probable to display no further BMI category change following a recorded decrease.
Data for subsequent changes in BMI category in participants who showed an initial decrease in BMI category for (a) women and (b) men: United kingdom of great britain and northern ireland, 2004–2014.
Annotation. BMI = body mass index. Data are presented by gender and initial BMI category.
DISCUSSION
Assay of primary care electronic wellness records for a big population-based sample of men and women over a ix-year period revealed that the probability of obese patients attaining normal weight was very low. The annual probability of patients with elementary obesity attaining a normal body weight was only 1 in 124 for women and one in 210 for men. The likelihood of attaining normal weight declined with increasing BMI category, with the everyman probability observed for morbidly obese patients. The smaller group of superobese patients was a departure from this trend just nevertheless showed a depression probability of attaining normal body weight. Although the probability of patients achieving a 5% reduction in body weight was considerably higher, the majority of these patients went on to regain lost weight, as evidenced by BMI records of greater than 95% of the initial value, within two to v years of the first record that was lower than 95% of the initial value.
These findings raise questions concerning whether current obesity handling frameworks, grounded in weight management programs accessed through primary care, may be expected to accomplish clinically relevant and sustained reductions in BMI for the vast majority of obese patients and whether they could be expected to do so in the future. The lack of sustained BMI reductions could exist driven past low intervention uptake rates or their lack of effectiveness.
In a previous study, we reported that weight loss interventions are currently offered only to a minority of patients in main intendance.4 Efforts are under way to meliorate this situation, with the proportion of patients with obesity offered multicomponent weight loss interventions included amid potential new indicators in the 2016–2017 consultation for the Clinical Commissioning Group Indicator Set.8 Notwithstanding, even when treatment is accessed, evidence suggests behavioral weight loss interventions focusing on caloric restriction and increased physical activity are unlikely to yield clinically pregnant reductions in body weight.five,9
A recent series of reviews documented the limited progress in reversing the global obesity epidemic and called for regulatory actions from governments every bit well as coordinated efforts across industry and society to reduce obesity.10–13 Dietz et al. warn that preventive strategies are unlikely to reduce weight in people living with severe obesity and stress the need for changes in the delivery of care for these patients.14 In combination with previous research, our written report highlights the current failures in combatting existing obesity cases at a population level.
Nosotros observed reductions in BMI category more frequently among patients with a higher baseline BMI, merely these decreases were more likely to exist followed by subsequent increases than further decreases or stability in BMI category. Weight cycling, evidenced past both increases and decreases in BMI category, was most common among men and women with baseline BMIs in the morbid obese category. Greater instability in weight trajectories among patients with higher BMIs has been reported previously.15 Weight cycling has been linked to a higher risk of morbidity and mortality than has stable obesity16–18 although testify of causality remains inconclusive.19
The college likelihood of decreases in BMI category and of v% weight loss among the more severely obese participants in our written report is consistent with results from clinical trials20 and previous cohort studies21 in which college BMI predicted greater weight loss. The increased probability of weight reduction among patients with more severe obesity may reflect more than authentic perceptions of personal weight status22,23 and higher treatment rates amid these patients. It is also possible that BMI decreases in severely obese patients reflect unintentional weight loss resulting from greater comorbidity.
The finding that a loftier proportion of patients experienced a menses of weight regain post-obit weight loss is also consequent with previous research. At least 50% of patients who accomplished five% weight loss were shown to have regained this weight inside 2 years. Information technology has previously been reported that approximately eighty% of people who intentionally achieve weight loss of 10% or more of their trunk weight volition regain that weight within a year.24
Strengths and Limitations
This report had the strengths of a large population-based accomplice with prolonged follow-upwardly. We have presented information for adults anile 20 years and older. Inspection of age-specific values revealed, equally expected, greater weight gain at younger ages and a somewhat greater tendency to weight loss at older ages. It was not possible to evaluate intentionality of weight loss. Previous studies have reported that the bulk of obese individuals would like to lose weight and that a large proportion is actively attempting to reduce their weight,25,26 so a relatively high level of intentionality amidst obese participants may be assumed.
Additionally, monitoring BMI among obese patients in primary care has been shown to predict handling positively.27 Patients in this study were required to have a minimum of 3 BMI measurements recorded, suggesting that an inflated proportion of patients in this sample may accept been involved in and interested in weight direction interventions. All the same, we acknowledge that unintentional weight loss was also included and might outcome from concrete disorders such equally cancer or psychological concerns such as bereavement.28–thirty Boosted in-depth analyses might evaluate patterns of weight modify in relation to comorbidity.
Recording trunk weight in main care is generally related to the opportunity to do so and depends on patients attention the practice. Nosotros admit that weight measurements in electronic health records may be associated with error and bias, including measurement error, misreckoning by indication if weight changes prompt weight measurements, variation between professionals and family practices in measurement recording,31 and weight management strategies.four A higher patient baseline BMI was associated with a higher frequency of BMI measurements recorded over the study period.
United kingdom general practices have contractual financial incentives to provide a register of adult patients who accept a BMI of 30 or greater kilograms per meters squared measured in the past fifteen months,32 which may lead to more frequent recording of BMI for obese patients. Nosotros reported on the recording of BMI in chief care in a previous report.31 For this study, we selected participants with a minimum of 3 BMI records. Nosotros admit that participants with fewer than three BMI records may evidence dissimilar patterns of weight change, and our results might exist biased through their omission. However, we believe that this is one of the largest studies yet reported on body weight changes in the general population.
The relatively high levels of comorbidity seen in obese compared with normal weight patients would also likely result in more than regular consultations and more frequent recording of BMI. However it is possible that patients from all BMI categories with 3 or more BMI measurements recorded over the 9-year study period represent a biased, less healthy sample compared with the general population. If this is the case, then unintentional weight loss, along with comorbidities contributing to weight gain such as mobility impairment, may have influenced BMI changes disproportionately in our sample.
Conclusions
Our findings signal that electric current nonsurgical obesity handling strategies are failing to achieve sustained weight loss for the majority of obese patients. For patients with a BMI of thirty or greater kilograms per meters squared, maintaining weight loss was rare and the probability of achieving normal weight was extremely low. Research to develop new and more constructive approaches to obesity management is urgently required.
Obesity treatment programs should prioritize prevention of farther weight gain along with the maintenance of weight loss in those who achieve it. Yet, in the absence of constructive interventions targeted at the individual level, the greatest opportunity for tackling the current obesity epidemic may be found exterior primary intendance. Research to develop wider reaching public health policies is needed to prevent obesity at the population level.
Acknowledgments
This research was supported by the UK National Institutes for Health Enquiry (NIHR) Wellness Services and Delivery Enquiry program (grant 12/5005/12). T. Prevost and M. C. Gulliford were supported by the NIHR Biomedical Inquiry Centre at Guy's and St Thomas' National Health Service (NHS) Foundation Trust and King's Higher London.
This written report was derived in part from data from the Clinical Practice Research Datalink obtained under license from the Great britain Medicines and Healthcare Products Regulatory Agency (MHRA).
Note. The funders did not appoint in designing or conducting the study; collecting, managing, analyzing, or interpreting information; or preparing, reviewing, or approving the article. The views, interpretations, and conclusions expressed in this article are those of the authors and not necessarily those of the NHS, the NIHR, the UK Department of Wellness, or the MHRA.
Homo Participant Protection
Institutional review board approval was received from the United kingdom of great britain and northern ireland Clinical Practice Inquiry Datalink Contained Scientific Informational Committee.
References
1. Danaei Grand, Finucane MM, Lu Y et al. National, regional, and global trends in fasting plasma glucose and diabetes prevalence since 1980: systematic analysis of health test surveys and epidemiological studies with 370 state-years and two.7 million participants. Lancet. 2011;378(9785):31–40. [PubMed] [Google Scholar]
2. Butland B Foresight; United kingdom of great britain and northern ireland Department of Innovation, Universities and Skills. Tackling Obesities: Future Choices. 2nd ed. London, Uk: Authorities Office for Science; 2007. [Google Scholar]
4. Booth HP, Prevost AT, Gulliford MC. Admission to weight reduction interventions for overweight and obese patients in United kingdom main care: population-based accomplice study. BMJ Open up. 2015;5(1):e006642. [PMC free article] [PubMed] [Google Scholar]
v. Berth HP, Prevost TA, Wright AJ, Gulliford MC. Effectiveness of behavioural weight loss interventions delivered in a primary intendance setting: a systematic review and meta-analysis. Fam Pract. 2014;31(6):643–653. [PMC free commodity] [PubMed] [Google Scholar]
half-dozen. Wadden TA, Butryn ML, Hong PS, Tsai AG. Behavioral treatment of obesity in patients encountered in primary care settings: a systematic review. JAMA. 2014;312(17):1779–1791. [PMC free article] [PubMed] [Google Scholar]
seven. Williams T, van Staa T, Puri S, Eaton S. Recent advances in the utility and use of the Full general Do Research Database equally an example of a UK principal care data resource. Ther Adv Drug Saf. 2012;3(2):89–99. [PMC gratuitous commodity] [PubMed] [Google Scholar]
nine. Dombrowski SU, Avenell A, Sniehotta FF. Behavioural interventions for obese adults with additional take a chance factors for morbidity: systematic review of effects on behaviour, weight and affliction hazard factors. Obes Facts. 2010;3(6):377–396. [PMC gratis article] [PubMed] [Google Scholar]
10. Kleinert S, Horton R. Rethinking and reframing obesity. Lancet. 2015;385(9985):2326–2328. [PubMed] [Google Scholar]
11. Huang TT, Cawley JH, Ashe M et al. Mobilisation of public support for policy actions to prevent obesity. Lancet. 2015;385(9985):2422–2431. [PubMed] [Google Scholar]
12. Hawkes C, Smith TG, Jewell J et al. Smart food policies for obesity prevention. Lancet. 2015;385(9985):2410–2421. [PubMed] [Google Scholar]
13. Roberto CA, Swinburn B, Hawkes C et al. Patchy progress on obesity prevention: emerging examples, entrenched barriers, and new thinking. Lancet. 2015;385(9985):2400–2409. [PubMed] [Google Scholar]
14. Dietz WH, Baur LA, Hall K et al. Management of obesity: improvement of health-care preparation and systems for prevention and care. Lancet. 2015;385(9986):2521–2533. [PubMed] [Google Scholar]
fifteen. Zajacova A, Ailshire J. Body mass trajectories and mortality among older adults: a joint growth mixture-discrete-time survival analysis. Gerontologist. 2014;54(ii):221–231. [PMC free article] [PubMed] [Google Scholar]
sixteen. Irish potato RA, Patel KV, Kritchevsky SB et al. Weight change, body composition, and take chances of mobility disability and bloodshed in older adults: a population-based cohort written report. J Am Geriatr Soc. 2014;62(viii):1476–1483. [PMC free article] [PubMed] [Google Scholar]
17. Rzehak P, Meisinger C, Woelke Chiliad, Brasche Southward, Strube G, Heinrich J. Weight change, weight cycling and mortality in the ERFORT Male Cohort Report. Eur J Epidemiol. 2007;22(10):665–673. [PubMed] [Google Scholar]
18. Wannamethee SG, Shaper AG, Walker M. Weight change, weight fluctuation, and mortality. Arch Intern Med. 2002;162(22):2575–2580. [PubMed] [Google Scholar]
19. Mehta T, Smith DL, Muhammad J, Casazza Thou. Impact of weight cycling on risk of morbidity and bloodshed. Obes Rev. 2014;15(eleven):870–881. [PMC free article] [PubMed] [Google Scholar]
xx. Teixeira PJ, Going SB, Sardinha LB, Lohman TG. A review of psychosocial pre-treatment predictors of weight control. Obes Rev. 2005;6(1):43–65. [PubMed] [Google Scholar]
21. Jackson SE, Beeken RJ, Wardle J. Predictors of weight loss in obese older adults: findings from the The states and the UK. Obes Facts. 2014;7(2):102–110. [PMC free article] [PubMed] [Google Scholar]
22. Gregory CO, Blanck HM, Gillespie C, Maynard LM, Serdula MK. Health perceptions and demographic characteristics associated with underassessment of torso weight. Obesity (Silver Spring) 2008;16(five):979–986. [PubMed] [Google Scholar]
23. Duncan DT, Wolin KY, Scharoun-Lee M, Ding EL, Warner ET, Bennett GG. Does perception equal reality? Weight misperception in relation to weight-related attitudes and behaviors among overweight and obese US adults. Int J Behav Nutr Phys Act. 2011;8(1):20. [PMC free article] [PubMed] [Google Scholar]
24. Wing RR, Phelan S. Long-term weight loss maintenance. Am J Clin Nutr. 2005;82(1):222S–225S. [PubMed] [Google Scholar]
25. Yaemsiri S, Slining MM, Agarwal SK. Perceived weight status, overweight diagnosis, and weight control among US adults: the NHANES 2003–2008 study. Int J Obes (Lond) 2011;35(8):1063–1070. [PubMed] [Google Scholar]
26. Nicklas JM, Huskey KW, Davis RB, Wee CC. Successful weight loss among obese U.Southward. adults. Am J Prev Med. 2012;42(5):481–485. [PMC free article] [PubMed] [Google Scholar]
27. Ma J, Xiao L, Stafford RS. Adult obesity and office-based quality of care in the U.s.a.. Obesity (Silver Bound) 2009;17(5):1077–1085. [PMC free article] [PubMed] [Google Scholar]
28. Reife CM. Involuntary weight loss. Med Clin North Am. 1995;79(2):299–313. [PubMed] [Google Scholar]
29. Stroebe One thousand, Schut H, Stroebe W. Wellness outcomes of bereavement. Lancet. 2007;370(9603):1960–1973. [PubMed] [Google Scholar]
30. Lankisch P, Gerzmann M, Gerzmann JF, Lehnick D. Unintentional weight loss: diagnosis and prognosis. The first prospective follow-upwardly study from a secondary referral centre. J Intern Med. 2001;249(1):41–46. [PubMed] [Google Scholar]
31. Berth HP, Prevost AT, Gulliford MC. Epidemiology of clinical body mass alphabetize recording in an obese population in primary care: a cohort report. J Public Health (Oxf) 2013;35(1):67–74. [PubMed] [Google Scholar]
32. The NHS Information Center. Quality and outcomes framework. 2011. Available at: http://www.qof.ic.nhs.u.k.. Accessed Jan 22, 2015.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4539812/
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