Skip to main content
SpringerLink
Log in

A systematic review of temporal body weight and dietary intake patterns in adults: implications on future public health nutrition interventions to promote healthy weight

  • Review
  • Published:
European Journal of Nutrition Aims and scope Submit manuscript

Abstract

Purpose

The global prevalence of overweight remains high; effective strategies that consider patterns of body weight changes to identify periods when adults are susceptible to weight gain are warranted. This systematic review aimed to investigate body weight patterns, and how they were associated with dietary intake and/or dietary behaviours (Prospero CRD42020161977).

Methods

Systematic literature search was conducted in the Medline, Embase, and CINAHL databases until November 2020. Observational studies in adults (18 years and over) that reported at least two measurements of weight and dietary intake in a year were included. Risk of bias was conducted using the Evidence Analysis Library by the Academy of Nutrition and Dietetics tool. This review included 16 unique studies after title, abstract, and full-text screening, and findings were narratively synthesised.

Results

Of the six studies conducted in the farming populations, five were conducted in countries with two seasons (dry vs. rainy seasons) and all studies observed higher body weight during the dry season (up to 3.1 kg difference between seasons). The remaining study was conducted in a sub-tropical country and did not observe temporal weight patterns. Higher dietary intake was also reported during the dry season in the tropical countries. In non-farming populations (n = 10), temporal patterns were also seen, where higher body weight and adiposity was observed during colder seasons (autumn and winter). However, the opposite was found in a study conducted in Iran, where higher weight was seen in summer. Concurrent with higher body weight, higher energy, fat, carbohydrate and soda consumption, and lower fiber and vegetable intake were observed.

Conclusion

Temporal weight and dietary patterns exist, and they were country- and context-specific; these patterns were also related to factors such as activity levels, seasons and occupation. Future interventions should consider temporal patterns in the design and delivery of timely and tailored dietary interventions to promote optimal body weight.

PROSPERO Registration

PROSPERO Registration: CRD42020161977.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Abarca-Gómez L, Abdeen ZA, Hamid ZA, Abu-Rmeileh NM, Acosta-Cazares B, Acuin C, Adams RJ, Aekplakorn W, Afsana K, Aguilar-Salinas CA (2017) Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128·9 million children, adolescents, and adults. The Lancet 390(10113):2627–2642

    Article  Google Scholar 

  2. Walls HL, Magliano DJ, Stevenson CE, Backholer K, Mannan HR, Shaw JE, Peeters A (2012) Projected progression of the prevalence of obesity in Australia. Obesity 20(4):872–878. https://doi.org/10.1038/oby.2010.338

    Article  PubMed  Google Scholar 

  3. Davis WA, Peters KE, Makepeace A, Griffiths S, Bundell C, Grant SFA, Ellard S, Hattersley AT, Paul Chubb SA, Bruce DG, Davis TME (2018) Prevalence of diabetes in Australia: insights from the Fremantle Diabetes Study Phase II. Intern Med J 48(7):803–809. https://doi.org/10.1111/imj.13792

    Article  PubMed  PubMed Central  Google Scholar 

  4. Stanaway JD, Afshin A, Gakidou E, Lim SS, Abate D, Abate KH, Abbafati C, Abbasi N, Abbastabar H, Abd-Allah F (2018) Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. The Lancet 392(10159):1923–1994

    Article  Google Scholar 

  5. Bruce DG, Davis WA, Davis TM (2005) Longitudinal predictors of reduced mobility and physical disability in patients with type 2 diabetes: the Fremantle Diabetes Study. Diabetes Care 28(10):2441–2447. https://doi.org/10.2337/diacare.28.10.2441

    Article  PubMed  Google Scholar 

  6. Australian Bureau of Statistics (2019) Causes of Death, Australia, 2018. Canberra

  7. Alvarez-Alvarez I, de Rojas JP, Fernandez-Montero A, Zazpe I, Ruiz-Canela M, Hidalgo-Santamaría M, Bes-Rastrollo M, Martínez-González MÁ (2018) Strong inverse associations of Mediterranean diet, physical activity and their combination with cardiovascular disease: the Seguimiento Universidad de Navarra (SUN) cohort. Eur J Prev Cardiol 25(11):1186–1197

    Article  Google Scholar 

  8. Mihrshahi S, Gow ML, Baur LA (2018) Contemporary approaches to the prevention and management of paediatric obesity: an Australian focus. Med J Aust 209(6):267–274

    Article  Google Scholar 

  9. Helander EE, Wansink B, Chieh A (2016) Weight gain over the holidays in three countries. N Engl J Med 375(12):1200–1202. https://doi.org/10.1056/NEJMc1602012

    Article  PubMed  Google Scholar 

  10. Tseng E, Zhang A, Shogbesan O, Gudzune KA, Wilson RF, Kharrazi H, Cheskin LJ, Bass EB, Bennett WL (2018) Effectiveness of policies and programs to combat adult obesity: a systematic review. J Gen Intern Med 33(11):1990–2001

    Article  Google Scholar 

  11. Muller AM, Blandford A, Yardley L (2017) The conceptualization of a just-in-time adaptive intervention (JITAI) for the reduction of sedentary behavior in older adults. Mhealth 3:37. https://doi.org/10.21037/mhealth.2017.08.05

    Article  PubMed  PubMed Central  Google Scholar 

  12. Terzimehić N, Schneegass C, Hussmann H (2018) Towards finding windows of opportunity for ubiquitous healthy eating interventions. In: International conference on persuasive technology. Springer, pp 99–112

  13. Goldstein SP, Evans BC, Flack D, Juarascio A, Manasse S, Zhang F, Forman EM (2017) Return of the JITAI: applying a just-in-time adaptive intervention framework to the development of m-health solutions for addictive behaviors. Int J Behav Med 24(5):673–682. https://doi.org/10.1007/s12529-016-9627-y

    Article  PubMed  PubMed Central  Google Scholar 

  14. Miller CK (2019) Adaptive intervention designs to promote behavioral change in adults: what is the evidence? Curr DiabRep 19(2):7

    Google Scholar 

  15. Spruijt-Metz D, Wen CK, O’Reilly G, Li M, Lee S, Emken B, Mitra U, Annavaram M, Ragusa G, Narayanan S (2015) Innovations in the use of interactive technology to support weight management. Curr Obes Rep 4(4):510–519

    Article  CAS  Google Scholar 

  16. Nahum-Shani I, Hekler EB, Spruijt-Metz D (2015) Building health behavior models to guide the development of just-in-time adaptive interventions: a pragmatic framework. Health Psychol 34:1209–1219. https://doi.org/10.1037/hea0000306

    Article  PubMed Central  Google Scholar 

  17. Nahum-Shani I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A, Murphy SA (2018) Just-in-time adaptive interventions (JITAIs) in mobile health: key components and design principles for ongoing health behavior support. Ann Behav Med 52(6):446–462. https://doi.org/10.1007/s12160-016-9830-8

    Article  PubMed  Google Scholar 

  18. Fentahun N, Belachew T, Coates J, Lachat C (2018) Seasonality and determinants of child growth velocity and growth deficit in rural southwest Ethiopia. BMC Pediatr 18(1):1–9

    Article  Google Scholar 

  19. Academy of Nutrition and Dietetics (2020) Evidence analysis manual: steps in the academy evidence analysis process. Academy of Nutrition and Dietetics. https://www.andeal.org/evidence-analysis-manual. Accessed 21 Aug 2020

  20. Wyse CA, Celis Morales CA, Ward J, Lyall D, Smith DJ, Mackay D, Curtis AM, Bailey ME, Biello S, Gill JM (2018) Population-level seasonality in cardiovascular mortality, blood pressure, BMI and inflammatory cells in UK biobank. Ann Med 50(5):410–419

    Article  Google Scholar 

  21. Loutan L, Lamotte J (1984) Seasonal variations in nutrition among a group of nomadic pastoralists in Niger. The Lancet 323(8383):945–947

    Article  Google Scholar 

  22. Abdullah M, Wheeler EF (1985) Seasonal variations, and the intra-household distribution of food in a Bangladeshi village. Am J Clin Nutr 41(6):1305–1313

    Article  CAS  Google Scholar 

  23. Adams A (1995) Seasonal variations in energy balance among agriculturalists in central Mali: compromise or adaptation? Eur J Clin Nutr 49(11):809–823

    CAS  PubMed  Google Scholar 

  24. Ategbo E, Van Raaij J, De Koning F, Hautvast J (1995) Resting metabolic rate and work efficiency of rural Beninese women: a 2-y longitudinal study. Am J Clin Nutr 61(3):466–472

    Article  CAS  Google Scholar 

  25. Kigutha HN, van Staveren WA, Hautvast JG (1998) Elderly under nutritional stress: a seasonal study on food consumption and nutritional status in Kenya. Int J Food Sci Nutr 49(6):423–433

    Article  Google Scholar 

  26. Murayama N (2005) Nutritional adaptation to seasonal climatic change: a study for rain-fed farmers in northeast Thailand. Environ Sci 12(3):133–144

    PubMed  Google Scholar 

  27. Murayama N, Ohtsuka R (1999) Seasonal fluctuation in energy balance among farmers in Northeast Thailand: the lack of response of energy intake to the change of energy expenditure. Eur J Clin Nutr 53(1):39–49

    Article  CAS  Google Scholar 

  28. Van Staveren WA, Deurenberg P, Burema J, De Groot LC, Hautvast J (1986) Seasonal variation in food intake, pattern of physical activity and change in body weight in a group of young adult Dutch women consuming self-selected diets. Int J Obes 10(2):133–145

    PubMed  Google Scholar 

  29. Lee CJ, Lawler GS, Panemangalore M, Street D (1987) Nutritional status of middle-aged and elderly females in Kentucky in two seasons: Part 1. Body weight and related factors. J Am Coll Nutr 6(3):209–215

    Article  CAS  Google Scholar 

  30. Bluher M, Hentschel B, Rassoul F, Richter V (2001) Influence of dietary intake and physical activity on annual rhythm of human blood cholesterol concentrations. Chronobiol Int 18(3):541–557. https://doi.org/10.1081/cbi-100103975

    Article  CAS  PubMed  Google Scholar 

  31. Ma Y, Olendzki BC, Li W, Hafner AR, Chiriboga D, Hebert JR, Campbell M, Sarnie M, Ockene IS (2006) Seasonal variation in food intake, physical activity, and body weight in a predominantly overweight population. Eur J Clin Nutr 60(4):519–528. https://doi.org/10.1038/sj.ejcn.1602346

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Wengreen HJ, Moncur C (2009) Change in diet, physical activity, and body weight among young-adults during the transition from high school to college. Nutr J 8(1):1

    Article  Google Scholar 

  33. Wagner DR, Larson JN, Wengreen H (2012) Weight and body composition change over a six-week holiday period. Eat Weight Disord 17(1):e54-56. https://doi.org/10.1007/bf03325328

    Article  CAS  PubMed  Google Scholar 

  34. Haghighatdoost F, Malekahmadi M, Onvani S, Ramezani-Jolfaie N, Azadbakht L (2018) Macronutrient composition and body mass index vary by season in college students. Prog Nutr 20(3):483–490

    Google Scholar 

  35. Kucukerdonmez O, Rakıcıoglu N (2018) The effect of seasonal variations on food consumption, dietary habits, anthropometric measurements and serum vitamin levels of university students. Prog Nutr 20(2):165–175

    CAS  Google Scholar 

  36. Morinaka T, Wozniewicz M, Jeszka J, Bajerska J, Limtrakul P-n, Makonkawkeyoon L, Hirota N, Kumagai S, Sone Y (2012) Comparison of seasonal variation in the fasting respiratory quotient of young Japanese, Polish and Thai women in relation to seasonal change in their percent body fat. J Physiol Anthropol 31(1):1–12

    Article  Google Scholar 

  37. Vartanian LR, Schwartz MB, Brownell KD (2007) Effects of soft drink consumption on nutrition and health: a systematic review and meta-analysis. Am J Public Health 97(4):667–675. https://doi.org/10.2105/AJPH.2005.083782

    Article  PubMed  PubMed Central  Google Scholar 

  38. Sayon-Orea C, Martinez-Gonzalez MA, Bes-Rastrollo M (2011) Alcohol consumption and body weight: a systematic review. Nutr Rev 69(8):419–431

    Article  Google Scholar 

  39. Schwingshackl L, Hoffmann G, Kalle-Uhlmann T, Arregui M, Buijsse B, Boeing H (2015) Fruit and vegetable consumption and changes in anthropometric variables in adult populations: a systematic review and meta-analysis of prospective cohort studies. PLoS ONE 10(10):e0140846

    Article  Google Scholar 

  40. Bray GA, Popkin BM (1998) Dietary fat intake does affect obesity! Am J Clin Nutr 68(6):1157–1173

    Article  CAS  Google Scholar 

  41. Sylvia LG, Bernstein EE, Hubbard JL, Keating L, Anderson EJ (2014) Practical guide to measuring physical activity. J Acad Nutr Diet 114(2):199–208

    Article  Google Scholar 

  42. Trost SG (2001) Objective measurement of physical activity in youth: current issues, future directions. Exerc Sport Sci Rev 29(1):32–36

    Article  CAS  Google Scholar 

  43. Yanovski JA, Yanovski SZ, Sovik KN, Nguyen TT, O’Neil PM, Sebring NG (2000) A prospective study of holiday weight gain. N Engl J Med 342(12):861–867. https://doi.org/10.1056/NEJM200003233421206

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Hull HR, Hester CN, Fields DA (2006) The effect of the holiday season on body weight and composition in college students. Nutr Metab 3(1):44. https://doi.org/10.1186/1743-7075-3-44

    Article  Google Scholar 

  45. Hull HR, Radley D, Dinger MK, Fields DA (2006) The effect of the Thanksgiving holiday on weight gain. Nutr J 5:29. https://doi.org/10.1186/1475-2891-5-29

    Article  PubMed  PubMed Central  Google Scholar 

  46. Cook CM, Subar AF, Troiano RP, Schoeller DA (2012) Relation between holiday weight gain and total energy expenditure among 40-to 69-y-old men and women (OPEN study). Am J Clin Nutr 95(3):726–731

    Article  CAS  Google Scholar 

  47. Schoeller DA (2014) The effect of holiday weight gain on body weight. Physiol Behav 134:66–69

    Article  CAS  Google Scholar 

  48. Díaz-Zavala RG, Castro-Cantú MF, Valencia ME, Álvarez-Hernández G, Haby MM, Esparza-Romero J (2017) Effect of the holiday season on weight gain: a narrative review. J Obes. https://doi.org/10.1155/2017/2085136

    Article  PubMed  PubMed Central  Google Scholar 

  49. Mason F, Farley A, Pallan M, Sitch A, Easter C, Daley AJ (2018) Effectiveness of a brief behavioural intervention to prevent weight gain over the Christmas holiday period: randomised controlled trial. BMJ (Clinical research ed). https://doi.org/10.1136/bmj.k4867

    Article  Google Scholar 

  50. Boutelle KN, Kirschenbaum DS, Baker RC, Mitchell ME (1999) How can obese weight controllers minimize weight gain during the high risk holiday season? By self-monitoring very consistently Health Psychol 18(4):364

    CAS  PubMed  Google Scholar 

  51. Watras AC, Buchholz AC, Close RN, Zhang Z, Schoeller DA (2007) The role of conjugated linoleic acid in reducing body fat and preventing holiday weight gain. Int J Obes (Lond) 31(3):481–487. https://doi.org/10.1038/sj.ijo.0803437

    Article  CAS  Google Scholar 

  52. Rich C, Griffiths LJ, Dezateux C (2012) Seasonal variation in accelerometer-determined sedentary behaviour and physical activity in children: a review. Int J Behav Nutr Phys Act 9(1):1–8

    Article  Google Scholar 

  53. Tucker P, Gilliland J (2007) The effect of season and weather on physical activity: a systematic review. Public Health 121(12):909–922. https://doi.org/10.1016/j.puhe.2007.04.009

    Article  CAS  PubMed  Google Scholar 

  54. Carson V, Spence JC (2010) Seasonal variation in physical activity among children and adolescents: a review. Pediatr Exerc Sci 22(1):81–92

    Article  Google Scholar 

  55. Ridgers ND, Salmon J, Timperio A (2015) Too hot to move? Objectively assessed seasonal changes in Australian children’s physical activity. Int J Behav Nutr Phys Act 12(1):1–8

    Article  Google Scholar 

  56. Turrisi TB, Bittel KM, West AB, Hojjatinia S, Hojjatinia S, Mama SK, Lagoa CM, Conroy DE (2021) Seasons, weather, and device-measured movement behaviors: a scoping review from 2006 to 2020. Int J Behav Nutr Phys Act 18(1):1–26

    Article  Google Scholar 

  57. Jahns L, Johnson LK, Scheett AJ, Stote KS, Raatz SK, Subar AF, Tande D (2016) Measures of diet quality across calendar and winter holiday seasons among midlife women: a 1-year longitudinal study using the automated self-administered 24-hour recall. J Acad Nutr Diet 116(12):1961–1969

    Article  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge Ms Christy Ting for her assistance in conducting additional literature search and performing title/abstract and full-text article screening.

Funding

RML is supported by a Postdoctoral Research Fellowship from the National Heart Foundation (ID102109) and an Emerging Leadership Fellowship (L1) from National Health and Medical Research Council (APP1175250). NDR is supported by a Future Leader Fellowship from the National Heart Foundation of Australia (ID 101895). No other funding was received to conduct this review.

Author information

Authors and Affiliations

  1. School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, 3220, Australia

    Sze-Yen Tan, Annie R. Curtis, Rebecca M. Leech, Nicola D. Ridgers, David Crawford & Sarah A. McNaughton

  2. Institute for Physical Activity and Nutrition (IPAN), Deakin University, 221, Burwood Highway, Burwood, VIC, 3125, Australia

    Sze-Yen Tan

Authors
  1. Sze-Yen Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Annie R. Curtis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rebecca M. Leech
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nicola D. Ridgers
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. David Crawford
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sarah A. McNaughton
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conception: all authors; literature search, article screening, data extraction, and quality assessment: ARC and S-YT; drafting manuscript: S-YT; critical review and revision for intellectual content: all authors.

Corresponding author

Correspondence to Sze-Yen Tan.

Ethics declarations

Conflict of interest

No conflict of interest.

Availability of data and materials

Not applicable.

Code availability

Not applicable.

Additional declarations for articles in life science journals that report the results of studies involving humans and/or animals

Not applicable.

Ethics approval

Not applicable.

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tan, SY., Curtis, A.R., Leech, R.M. et al. A systematic review of temporal body weight and dietary intake patterns in adults: implications on future public health nutrition interventions to promote healthy weight. Eur J Nutr 61, 2255–2278 (2022). https://doi.org/10.1007/s00394-021-02791-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00394-021-02791-x

Keywords

Search

Navigation