Trends in obesity defined by body mass index among adults before and during the COVID-19 pandemic: a repeated cross-sectional study of the 2009–2023 Canadian Community Heath Surveys

Abstract

Background:

The COVID-19 pandemic affected health behaviours and the social determinants of health. We sought to describe trends in the prevalence in body mass index (BMI) categories before and during the COVID-19 pandemic among adults in Canada.

Methods:

We conducted a repeated cross-sectional study of adults in the 2009–2023 Canadian Community Health Surveys. We compared changes after the onset of the COVID-19 pandemic (April 2020 to December 2023) to an 11-year prepandemic period (January 2009 to March 2020). We calculated odds ratios (ORs) and absolute percentages from, respectively, weighted logistic and linear regression models.

Results:

Our unweighted analytic sample included 746 250 adults from the 2009–2023 surveys. The prevalence of BMI-defined obesity increased from 24.95% in 2009 to 32.69% in 2023 (absolute increase 7.74%). The COVID-19 pandemic period was associated with an adjusted annual increase in the relative odds of obesity that was 1.02 (95% confidence interval [CI] 1.01–1.04) times greater than the prepandemic period. The absolute rate of increase of BMI-defined obesity nearly doubled during the pandemic, with an annual average excess rate of 0.44 (95% CI 0.14–0.74) percentage points. Class II and III obesity increased at a greater absolute rate than class I, indicating a shift toward more severe obesity. The relative increase in class III obesity was greater among young adults and females.

Interpretation:

Since the COVID-19 pandemic, the prevalence of BMI-defined obesity, and especially class III obesity, increased at a faster rate than before the pandemic. Some groups that historically had lower levels of obesity were disproportionately affected during the pandemic.

Studies in global populations have suggested a modest increase in BMI and BMI-defined obesity during the COVID-19 pandemic.^1–3 Early in the pandemic obesity was recognized as a risk factor for COVID-19 severity and death;⁴ however, the broader effects of the COVID-19 pandemic and associated public health restrictions on chronic diseases and their risk factors at the population level received less focus initially. The pandemic led to unprecedented and rapid changes in the daily lives of people in Canada, including adverse changes in sedentary time, physical activity, diet, food insecurity, stress, mental health, and the worsening of many socioeconomic factors, including job loss and higher costs of living.^5–7 Many of these upstream and intermediate factors have been associated with a greater risk of developing obesity.^8,9 Before the pandemic, trends toward increasing body mass index (BMI) were observed in Canada, with a substantial shift toward more severe obesity.^9–11 Severe obesity is strongly associated with increased risk of morbidity and death.¹² However, population-based trends in BMI before and after the onset of the COVID-19 pandemic in Canada have not yet been reported.

Excess body weight is an established risk factor that affects the health care system, and the health and well-being of Canada’s population.¹³ At the individual and clinical levels, the measurement of obesity is complex and should consider more than BMI alone.^14,15 The use of BMI to define obesity has well-known limitations^14–17 and, although BMI is correlated with body fat,^18,19 it is not a direct measure of body fat or health, and common cut points used to define obesity are not appropriate for people of all ethnicities.^14,20,21 Not all individuals with a BMI of 30 or higher will have impaired health or increased risk of death, and some individuals with a BMI below 30 may also have obesity.¹⁸ However, for population-level screening and surveillance, the use of BMI categories as a proxy for obesity in adults continues to be recommended.^9,14

The primary objective of this study was to describe the change in BMI and BMI-defined obesity before and during the COVID-19 pandemic, from 2009 to 2023, among adults in Canada. Secondary objectives were to describe the prevalence of BMI-defined obesity severity, and to explore differences by sex, age, province, household income, and race.

Methods

Study design and setting

We conducted a population-based repeated cross-sectional study using Canadian Community Health Survey (CCHS) data from 2009 to 2023 among adults aged 18 years and older.²² The CCHS is conducted annually throughout the year by Statistics Canada, with a range of 42 000 to 65 000 participants per year, and uses a multistage sampling strategy that is representative of more than 97% of the population in Canada older than 12 years.²² Data collection is by telephone and in-person interviews, and an online electronic questionnaire was introduced in 2022. We accessed individual-level data at the Statistics Canada Research Data Centre at McMaster University. The target population for the CCHS is Canadians older than 12 years from all provinces and territories; people living on reserves, full-time members of Canadian Forces, and institutionalized populations are excluded from the survey. However, for the 2023 cycle, the target population was Canadians older than 17 years, as those aged 12–17 years were included in the Canadian Health Survey on Children and Youth. For this study, we excluded people who were pregnant or breastfeeding and people younger than 18 years, given limitations with the validity of BMI in these populations. We also excluded respondents living in the territories since data from these areas are not valid annually and need to be used in 2-year periods owing to small sample sizes. We also excluded respondents with missing BMI data and those with extreme BMI values (< 12 or > 70), which may be errors.²³

Data collection paused in mid-March 2020 because of the COVID-19 pandemic and was not resumed until September 2020. From September to December 2020, a sample equivalent to the second, third, and fourth quarters was collected over approximately 5 weeks each. Consequently, the annual 2020 data include some pre-COVID-19 data, but most data were collected after the onset of the COVID-19 pandemic. The CCHS response rate ranged from 54.0% to 81.3% between 2009 and 2019. However, in 2020 and 2021 the response rate decreased to 24.6% and 24.1%, respectively, and in 2022 and 2023 the response rates were 42.7% and 40.6%, respectively.²²

Measurement of outcome

Body mass index was calculated from self-reported weight in kilograms, divided by height in metres squared. Validated correction equations based on sex-specific regression models were applied to BMI to adjust for bias in self-reported height and weight in the CCHS.^24,25 These equations, which were last updated in 2011, were validated against a CCHS subsample with measured height and weight collected by trained interviewers. We categorized observations into BMI categories defined by the World Health Organization, namely underweight (BMI < 18.5), normal (18.5 ≤ BMI < 25), overweight (25 ≤ BMI < 30), and obesity (BMI ≥ 30).²⁶ We further categorized those with obesity by severity into class I (30 ≤ BMI < 35), class II (35 ≤ BMI < 40) and class III obesity (≥ 40). We used different thresholds for people of Asian (South Asian, Chinese, Filipino, Southeast Asian, Korean, and Japanese) descent (underweight [BMI < 18.5], normal [18.5 ≤ BMI < 23], overweight [23 ≤ BMI < 27.5], and obesity [BMI ≥ 27.5]; class I [27.5 ≤ BMI < 32.5], class II [32.5 ≤ BMI < 37.5], and class III [≥ 37.5] obesity).^14,20,21

Other variables

The main exposure of interest was the onset of the COVID-19 pandemic. A COVID-19 binary indicator variable was created based on the response date that classified respondents as “prepandemic” (Jan. 1, 2009, to Mar. 2020) or “postpandemic onset” (Apr. 1, 2020, to Dec. 31, 2023). We stratified analyses of trends in obesity by the following variables, which we selected based on the literature: sex, household income, race or ethnicity, province, and any chronic condition (defined as heart disease, stroke, cancer, high blood pressure, diabetes, and arthritis). The collection of data on race and ethnicity was similar over time, whereby participants were asked to report their own racial or cultural groups and asked to mark all that applied from a list of 12 response options, including “other – specify.” We categorized racial and ethnic groups based on the most common responses and collapsed the remainder, including those who chose multiple options, into 1 category owing to small sample sizes. We stratified by race or ethnicity as a proxy for systemic racism and to investigate possible health inequities. Details are in Appendix 1, Supplemental methods, available at www.cmaj.ca/lookup/doi/10.1503/cmaj.241421/tab-related-content.

Statistical analysis

Sampling weights were applied to yield representative estimates at the provincial and national levels. We conducted statistical analyses using Stata version 18.0. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) from logistic regression models to assess the relative impact of the pandemic on each BMI category. We included a linear trend with survey year as the unit of change (i.e., 2009 = −11, 2020 = 0, 2023 = 3) and allowed a change in trend after the onset of the COVID-19 pandemic. The interaction of the linear trend with the COVID-19 binary variable indicates a change in the trend — the excess impact of the COVID-19 pandemic on BMI categories — which was our primary outcome of interest. Additionally, we applied a linear probability model to the identical set of predictors and reported the resulting changes in absolute probabilities as marginal effects. Details on the statistical analysis and study methodology are provided in Appendix 1.

Ethics approval

Ethics approval by an institutional review board was not required because the anonymous microdata were analyzed within Statistics Canada’s Research Data Centre at McMaster University.

Results

Over the 15 years of this study, the total unweighted sample size before exclusions was 870 390 participants (Figure 1). After excluding participants who were younger than 18 years (n = 62 120), living in the territories (n = 8340), pregnant or breast-feeding (n = 7340), missing BMI (n = 46 000), or BMI outliers (n = 340), the final analytic sample size was 746 250 participants. Characteristics of the study population by year are shown in Table 1. Distribution by sex and province were relatively constant over the 15 years studied, but there were changes in age and race and ethnicity, with a higher proportion of older adults and of Asian and Black participants in 2023 than in 2009. Additional descriptions of the study population and exclusions are provided in Appendix 1, Supplemental Tables 1–3. As shown in Figure 2 and Table 2, the prevalence of people with BMI-defined obesity increased from 24.95% in 2009 to 32.69% in 2023, an absolute increase of 7.74%. The prevalence of people who were under-weight increased from 1.34% in 2009 to 1.64% in 2023. In contrast, the prevalence of people with normal weight (34.97%–28.05%) and overweight (38.74%–37.62%) decreased. From 2009 to 2023, the prevalence of people with class I (17.38%–20.11%), class II (5.21%–7.65%), and class III (2.37%–4.93%) obesity increased, with absolute increases of 2.73%, 2.44% and 2.56%, respectively (Table 2).

Figure 1:

Flowchart for unweighted analytical sample (rounded by nearest 10) of Canadian Community Health Survey (CCHS) participants from 2009 to 2023. *We excluded people from the territories because of the small sample size (n = 8340 over the 15-year study period); numbers from territories cannot be reported annually and must be used only in 2-year increments. Although we recognize this is not ideal, it is a common approach for CCHS studies of trends over time. See Related Content for accessible version. Note: BMI = body mass index.

Table 1:

Respondent characteristics from the Canadian Community Health Survey by year

Characteristic	Respondents, %*
	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
Unweighted no. of respondents	51 280	52 520	52 650	51 790	53 900	53 470	43 870	47 410	48 670	46 340	56 880	36 980	42 630	58 460	49 400
Age, yr
18–29	20.27	20.54	20.52	20.31	20.06	19.78	19.36	18.80	19.05	19.04	18.46	17.51	17.61	17.48	16.91
30–39	16.73	15.61	16.30	16.00	16.40	16.07	16.59	16.90	17.18	17.04	17.66	18.58	17.27	16.81	18.03
40–49	20.31	20.32	18.60	18.31	18.01	17.18	17.70	17.41	16.75	16.64	16.88	16.55	16.89	16.67	16.74
50–59	18.96	19.26	19.35	19.22	19.57	19.75	19.20	19.02	18.43	18.10	17.62	16.51	16.18	16.43	15.34
60–69	13.16	13.29	14.16	14.91	14.42	15.37	15.59	15.84	15.83	16.20	15.74	16.57	17.27	16.44	16.81
70–79	7.23	7.43	7.33	7.62	7.90	8.26	8.14	8.67	9.09	9.28	9.66	10.23	10.44	11.23	11.13
≥ 80	3.33	3.54	3.74	3.62	3.64	3.59	3.43	3.36	3.68	3.70	3.98	4.06	4.34	4.94	5.04
Sex
Female	50.82	50.97	50.78	50.88	50.89	50.77	50.94	51.11	50.98	50.93	50.35	50.24	50.86	51.21	50.79
Male	49.18	49.03	49.22	49.12	49.11	49.23	49.06	48.89	49.02	49.07	49.65	49.76	49.14	48.79	49.21
Race or ethnicity
Asian	9.41	10.30	10.09	11.26	11.21	11.52	10.74	11.60	12.16	12.90	12.72	13.49	14.96	15.35	16.47
Black	2.21	2.18	1.99	2.26	2.43	2.52	2.71	2.27	2.42	2.50	2.76	2.83	3.10	3.77	3.46
White	82.57	80.66	80.57	78.73	78.34	77.89	76.47	76.79	77.15	76.15	74.77	77.52	75.03	74.61	73.49
All others	5.81	6.87	7.35	7.75	8.02	8.06	10.09	9.34	8.26	8.45	9.75	6.16	6.91	6.27	6.58
Province
NL	1.58	1.55	1.53	1.52	1.51	1.56	1.51	1.52	1.51	1.49	1.45	1.46	1.42	1.44	1.41
PEI	0.40	0.42	0.42	0.43	0.42	0.41	0.41	0.42	0.41	0.42	0.42	0.43	0.43	0.45	0.45
NS	2.82	2.83	2.79	2.79	2.71	2.70	2.71	2.70	2.68	2.66	2.63	2.62	2.63	2.69	2.66
NB	2.30	2.24	2.25	2.21	2.18	2.13	2.08	2.14	2.11	2.10	2.03	2.06	2.06	2.12	2.14
QC	23.80	23.81	23.71	23.68	23.61	23.76	23.80	24.15	23.87	23.63	23.67	23.33	22.97	22.55	22.21
ON	38.96	38.93	38.74	38.60	38.50	38.29	38.56	38.05	38.23	38.67	38.73	38.68	38.91	39.26	39.55
MB	3.39	3.34	3.40	3.37	3.41	3.35	3.34	3.31	3.37	3.37	3.37	3.35	3.33	3.31	3.28
SK	2.81	2.88	2.83	2.89	2.89	2.95	2.89	2.96	2.96	2.92	2.92	2.93	2.82	2.82	2.80
AB	10.38	10.70	10.80	11.01	11.07	11.46	11.57	11.50	11.56	11.52	11.56	11.46	11.36	11.24	11.45
BC	13.57	13.30	13.53	13.50	13.71	13.39	13.12	13.25	13.30	13.23	13.21	13.67	14.07	14.12	14.05

^*Unless indicated otherwise. Percentage of respondents weighted to the Canadian target population.

Figure 2:

(A) Absolute percent change and (B) the unadjusted prevalence of body mass index categories among adults in Canada, 2009–2023. Supporting data are presented in Table 2. Note: CI = confidence interval.

Table 2:

Weighted prevalence of BMI categories among adults from the Canadian Community Health Survey by year

BMI category	Weighted prevalence, %
	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020	2021	2022	2023
Underweight	1.34	1.29	1.28	1.32	1.48	1.44	1.30	1.25	1.35	1.48	1.60	1.67	1.66	1.60	1.64
Normal	34.97	34.14	34.54	33.54	32.95	32.90	32.53	32.31	31.70	31.16	30.87	30.26	29.02	29.34	28.05
Overweight	38.74	38.93	37.97	38.77	38.35	37.22	38.42	37.87	38.21	38.42	37.99	37.68	37.53	36.69	37.62
Obesity	24.95	25.64	26.21	26.36	27.22	28.44	27.75	28.57	28.74	28.94	29.54	30.39	31.79	32.36	32.69
Class I	17.38	17.67	18.18	18.42	18.78	19.09	18.85	19.22	19.09	19.38	19.39	19.93	20.78	20.39	20.11
Class II	5.21	5.39	5.48	5.29	5.52	6.46	6.00	6.35	6.23	6.29	6.56	6.81	7.05	7.65	7.65
Class III	2.37	2.58	2.55	2.65	2.93	2.89	2.91	3.00	3.42	3.27	3.59	3.64	3.96	4.32	4.93

Note: BMI = body mass index.

The average annual relative increase in the adjusted odds of BMI-defined obesity in the prepandemic period was 1.03 (95% CI 1.03 to 1.03). After the onset of the pandemic, the excess annual relative increase was 1.02 (95% CI 1.01 to 1.04) times greater than during the prepandemic period, after adjustment for sex, age, race or ethnicity, and province (Table 3). Results were similar for unadjusted and adjusted models.

Table 3:

Relative and absolute change for the associations between year, COVID-19 pandemic period, and BMI categories from weighted unadjusted and adjusted regression models for adults from the Canadian Community Health Survey from 2009 to 2023

Model	Underweight	Normal weight	Overweight	Obesity
Relative change, OR (95% CI)
Unadjusted
Prepandemic annual change (per yr)	1.02 (1.01 to 1.03)	0.98 (0.98 to 0.98)	1.00 (0.99 to 1.00)	1.02 (1.02 to 1.03)
Excess change postpandemic onset (COVID-19 × trend)*	1.00 (0.94 to 1.06)	0.98 (0.97 to 1.00)	1.00 (0.98 to 1.01)	1.02 (1.00 to 1.03)
Adjusted†
Prepandemic annual change (per yr)	1.03 (1.01 to 1.04)	0.98 (0.97 to 0.98)	0.99 (0.99 to 0.99)	1.03 (1.03 to 1.03)
Excess change postpandemic onset (COVID-19 × trend)*	0.97 (0.92 to 1.04)	0.98 (0.97 to 1.00)	1.00 (0.99 to 1.01)	1.02 (1.01 to 1.04)
Absolute change, % (95% CI)
Unadjusted
Prepandemic annual change (per yr)	0.03 (0.01 to 0.05)	−0.42 (−0.48 to −0.35)	−0.08 (−0.15 to −0.01)	0.47 (0.41 to 0.53)
Excess change postpandemic onset (COVID-19 × trend)*	0.00 (−0.08 to 0.09)	−0.31 (−0.60 to −0.02)	−0.11 (−0.42 to 0.19)	0.42 (0.13 to 0.71)
Adjusted†
Prepandemic annual change (per yr)	0.04 (0.02 to 0.06)	−0.45 (−0.52 to −0.39)	−0.20 (−0.26 to −0.13)	0.61 (0.55 to 0.67)
Excess change postpandemic onset (COVID-19 × trend)*	−0.07 (−0.16 to 0.02)	−0.34 (−0.64 to −0.05)	−0.02 (−0.35 to 0.30)	0.44 (0.14 to 0.74)

Note: BMI = body mass index, CI = confidence interval, OR = odds ratio.

^*Interaction between COVID-19 pandemic indicator variable (1 = after March 2020; 0 = March 2020 and before) and linear trend (In the trend, year of survey is the unit ofchange, e.g., −11 = 2009, −5 = 2016, 0 = 2020, 3 = 2022). The effect estimate can be interpreted as the average relative odds in annual increase postpandemic. Our preferredmodel had a slope change at the start of the COVID-19 period, with no intercept shift. However, we also modelled an intercept shift (Appendix 1, Supplemental Table 14). These results were similar. Employing both slope and intercept changes was not feasible with only 3 years of data after 2020.

^†Adjusted for age, race or ethnicity, province, income quintile, education, and sex.

The prepandemic adjusted absolute annual percentage point increase in the prevalence of BMI-defined obesity was 0.61% (95% CI 0.55% to 0.67%), with an excess annual increase of 0.44% after the onset of the pandemic (95% CI 0.14% to 0.74%) (Table 3). In the years after the pandemic commenced, obesity increased by slightly more than 1 percentage point per year, which is around twice the prepandemic rate of increase. For the underweight category, the adjusted prepandemic annual absolute increase was 0.04% (95% CI 0.02% to 0.06%), and there was no evidence of an excess increase during the pandemic (−0.07%, 95% CI −0.16% to 0.02%). For both the adjusted and unadjusted models, the absolute percentage of the population in the normal weight category declined, on average, each year before the pandemic (unadjusted −0.42%, 95% CI −0.48% to −0.35%; adjusted −0.45%, CI −0.52% to −0.39%); after the onset of COVID-19, the average annual rate of decline steepened (unadjusted excess decline −0.31%, 95% CI −0.60% to −0.02%; adjusted excess decline −0.34%, 95% CI −0.64% to −0.05%) (Table 3).

Stratified analyses revealed that the unadjusted prevalence of BMI-defined obesity was higher among males (26.69%) than females (23.15%) with a difference of 3.54% (p < 0.001) in 2009, but this difference narrowed during the pandemic with the prevalence of obesity in females approaching that of males for the first time in 2023 (33.64% v. 31.74%, p = 0.008) (Figure 3 and Appendix 1, Supplemental Tables 4 and 5). The absolute increase in obesity from 2009 to 2023 was greater among females (8.59%) than males (6.93%), although the difference in the increase was not statistically significant (p = 0.09) (Figure 3). The prevalence of class II and III BMI-defined obesity also increased markedly from 2009 to 2023, and both the prevalence and the increase in prevalence were greater among females (Figure 3). Although the rise in class III obesity among females relative to males during the study period was statistically significant (p < 0.01), the increase in class II obesity was not (p = 0.3). Smoothed histograms (density plots) of the population distribution of BMI for males and females over time illustrated a lower peak in the BMI distribution for females, but females also exhibited greater increases in recent years, especially in the upper tail, suggesting a greater shift toward severe obesity (Figure 4).

Figure 3:

(A) Absolute percent change and the (B) unadjusted prevalence of overweight and obesity defined by body mass index (BMI), including class I, II, and III obesity, among male adults in Canada, 2009–2023. (C) Absolute percent change and the (D) unadjusted prevalence of BMI-defined overweight and obesity, including class I, II, and III obesity, among female adults in Canada, 2009–2023. Supporting data are presented in Appendix 1, Supplementary Tables 4 and 5. Note: CI = confidence interval.

Figure 4:

Distribution of body mass index (BMI) as a continuous measure among (A) males and (B) females from 2010 to 2014, 2014 to 2019, and 2021 to 2023.

Over the 15-year study period, the prevalence of obesity was highest among the middle-aged groups (those aged 40–49, 50–59, and 60–69 years) (Figure 5), and this was consistent among males and females (Appendix 1, Supplemental Figure 3 and Supplemental Table 6) although a Wald test showed that these age groups were not statistically different from the others. However, both during the COVID-19 pandemic and over the entire study period, the greatest increase in obesity was observed among younger adults. The intersection between age and sex revealed that young females experienced greater increases than other groups, with an increase of nearly 9 percentage points (13.11%–21.71%) for females aged 18–29 years, compared with 6 percentage points for males aged 18–29 years (18.31%–24.36%), although the differences in these increases were not statistically significant (p = 0.3) (Appendix 1, Supplemental Table 6).

Figure 5:

(A) Absolute percent change and (B) unadjusted prevalence of obesity defined by body mass index among adults in Canada, 2009–2023, by age group. Supporting data are presented in Appendix 1, Supplementary Table 6.

Results of the stratified analyses by race and ethnicity (Figure 6 and Appendix 1, Supplemental Table 7) suggest that the prevalence of obesity was greatest among people who self-identified as White or Black, compared with those who identified as Asian (p < 0.001), with fairly consistent trends over time. An increase in the prevalence of obesity was observed in most provinces over the study period, but the small sample sizes and high variability in some provinces limited our interpretation of the trends (Appendix 1, Supplemental Figure 7 and Supplemental Table 8). Stratified analyses for the prevalence of BMI-defined obesity by income (Appendix 1, Supplemental Figure 8 and Supplemental Table 9) revealed few differences in the trend, but the prevalence of obesity tended to be lowest among people in the highest income quintile.

Figure 6:

(A) Absolute percent change and (B) the unadjusted prevalence of obesity defined by body mass index among adults in Canada, 2009–2023, by race or ethnicity. Supporting data are presented in Appendix 1, Supplemental Table 7. Note: CI = confidence interval.

Lastly, more than 50% of people with BMI-defined obesity did not have any chronic conditions, while about 40%–45% had 1–2 chronic conditions and 5%–10% had 3–6 chronic conditions (Figure 7). These patterns were relatively stable over time.

Figure 7:

Prevalence of obesity defined by body mass index among adults in Canada, 2009–2023, by number of chronic conditions (defined as heart disease, stroke, cancer, high blood pressure, diabetes, and arthritis). About 1.41% observations had missing values for chronic conditions.

Discussion

In 2023, 32.69% of adults in Canada (10.6 million people) had a BMI of 30 or higher (or > 27.5 among people of Asian descent). This was an absolute increase of nearly 8% from 2009, when the prevalence was 24.95%. Compared with the average increase during the 11 years before the pandemic, the prevalence of obesity increased at a greater rate during the 4 years after the onset of the COVID-19 pandemic (2020–2023), suggesting that the COVID-19 pandemic and associated public health restrictions may have adversely affected obesity prevalence in Canada. However, certain subgroups of the population showed some evidence that this increase may have started before the pandemic and additional explanations for this increase should be considered. Further, the relative increases in class II and class III obesity were substantial, suggesting a shift toward more severe obesity, which is concerning from a clinical perspective and may have important implications for both population health and health care utilization. We observed important subgroup differences, with several groups that had a lower historical prevalence of obesity showing a substantial increase during the pandemic, including females and young adults. This raises concerns about potential adverse long-term consequences.

Our results are consistent with prepandemic studies involving CCHS data that demonstrated a consistent upward trend in the prevalence of obesity from 1985 to 2011¹⁰ and from 2005 to 2017/18.¹¹ Our findings demonstrate that the actual prevalence of obesity exceeded projected estimates.¹⁰ Our analysis showed an approximately linear increase in obesity during the 11 years before the pandemic and also showed that the COVID-19 effect was best modelled as a linear slope change. However, future years of data may increase precision, and the choice between modelling the COVID-19 shock as a slope or intercept shift should be re-evaluated. Our overall findings of an increase in obesity during the COVID-19 pandemic are consistent with systematic reviews of studies from several other countries and populations. ^1,3 Although we found no evidence of a significant excess increase in the prevalence of people who were underweight during the pandemic period specifically, we did observe a small increase throughout the study period. Although uncommon in Canada, BMI-defined underweight can also be associated with adverse health outcomes. Any interventions to reduce or reverse the trend of increasing obesity should consider possible unintended or adverse consequences of messaging related to eating disorders and weight stigma.²⁷

Future studies are needed to understand the longer-term trends in obesity following the COVID-19 pandemic, and specifically, to evaluate whether the more steeply increasing trend in obesity remains or whether it returns to the prepandemic norm. Potential causes of the observed increase during the pandemic should also be explored, including both upstream or systemic causes and more proximal or individual-level determinants of health. It is especially important for future studies to consider the potential causes with respect to the observed health inequities. For example, the observed trends among females and racialized and younger adults may be driven by increased stress or adverse mental health effects related to occupation or caregiving status during the pandemic. Understanding drivers would be useful for informing both obesity prevention interventions and to mitigate longer-term adverse effects of public health restrictions during public health disasters.²⁸ We were not able to evaluate medication usage, but glucagon-like peptide-1 (GLP-1) receptor agonists for treatment of diabetes and weight loss were introduced in Canada during the study period.²⁹ Although these medications were not widely available for obesity treatment during most of the study period, we cannot rule out the possibility that medication usage may have mitigated the postpandemic trends.

Limitations

Potential limitations include the repeated cross-sectional design, instead of longitudinal follow-up of the same people, and changes in response rates over time. Although our descriptive data suggest few changes in the sample over time, it is unknown whether the decreased response rate during the COVID-19 pandemic was a source of bias. We observed some differences between included participants and those excluded because of missing or invalid BMI; included participants were more likely to be male and have higher income, and they were less likely to have any chronic conditions or be older. It is also a limitation that we had to exclude people from the territories owing to the small sample size and since numbers cannot be reported annually. Although self-reported height and weight are highly correlated with measured anthropometric values, systematic differences in self-reports can bias results. We adjusted for this source of error using validated correction estimates;^24,25 however, these correction equations are old and corrected self-reports may still underestimate actual BMI values and possibly bias our results. Obesity was defined using BMI alone and we relied on BMI thresholds that have many recognized limitations, including that they were not developed for racially diverse populations;¹⁵ however, we did apply BMI thresholds specific to Asian populations, which resulted in a higher estimate of people with overweight and obesity among respondents of Asian descent than is usually observed. A future approach may be to incorporate measures of health in addition to body size when measuring obesity and classifying disease severity.^14,30

Conclusion

The results of our large population-based study demonstrated that rates of BMI-defined obesity continue to increase among adults in Canada, and increased at a higher rate following the onset of the COVID-19 pandemic. Specific subgroups of the population were affected more than others, particularly females and younger adults. Investment in research and interventions to prevent and treat obesity in Canada are critical and should be an urgent priority for policy-makers.