Impact of the COVID-19 pandemic on CVD prevention between different socioeconomic groups in Switzerland

Background The COVID-19 pandemic disrupted the continuing management of cardiovascular disease (CVD) risk factors in the population. Socioeconomic status (SES) is a major determinant of health. Whether the COVID-19 pandemic increased, the SES gap in CVD risk factors is unknown. Aims To compare the management of CVD risk factors and the SES gap before and during the pandemic. Methods Cross-sectional study conducted between 2018 and 2021 in Lausanne, Switzerland. Prevalence, awareness, treatment and control rates of hypertension, dyslipidaemia and diabetes were compared between the periods before (N=2416, 45.2% men, 65.3±9.8 years) and during (N=776, 44.5% men, 63.9±9.1 years) the COVID-19 pandemic. SES was defined by education and categorised as low (compulsory or apprenticeship), middle (high school) and high (university). Results After multivariable analysis, the prevalence of hypertension increased, and awareness decreased during the pandemic: OR and (95% CI) 1.26 (1.04 to 1.53) and 0.70 (0.53 to 0.94), respectively. For dyslipidaemia, prevalence decreased during the pandemic 0.82 (95% CI 0.69 to 0.98); awareness did not change. For diabetes, prevalence did not change but awareness increased 5.76 (95% CI 1.23 to 27.04). No differences were found before and during the pandemic regarding treatment and control for all CVD risk factors. Relative to high SES, a decrease in hypertension awareness among middle SES categories was observed during the pandemic (OR and 95% CI 1.11 (0.73 to 1.69) before and 0.45 (95% CI 0.23 to 0.85) during, p for interaction<0.05), while no other changes were found. Conclusion Prevalence and management of CVD risk factors changed little during the pandemic. The SES gap did not increase except for hypertension awareness.


INTRODUCTION
The burden of cardiovascular diseases (CVD) had been on the rise in Switzerland with the ageing population 1 and escalating multimorbidity. 2CVD is caused by major risk factors such as hypertension, dyslipidaemia, smoking and diabetes; European guidelines regarding the prevention of CVD by tackling those risk factors have been issued. 36][7] Management of CVD risk factors also shows a socioeconomic gradient, subjects with a higher socioeconomic status (SES) presenting with higher control levels than subjects of lower SES. 8This leads to a considerable loss of opportunity among the lowest SES groups, who present with higher CVD rates, and earlier CVD events than higher SES groups. 9he COVID-19 pandemic posed a substantial global healthcare crisis.As of 11 October 2022, there have been over 630 million confirmed cases of COVID-19, and over 6.5 million deaths worldwide. 10As a response to the unprecedented rapidly spreading pandemic, containment and mitigation measures were done, leading to an inverse impact on the CVD services of most countries. 11n addition to exacerbating underlying CVD through direct and indirect effects, the COVID-19 crisis has also reinforced social

WHAT IS ALREADY KNOWN ON THIS TOPIC
⇒ The COVID-19 pandemic and the restrictive measures posed an inverse impact on the cardiovascular disease (CVD) services of most countries.Additionally, management of CVD risk factors shows a socioeconomic gradient; subjects with a higher socioeconomic status (SES) present with higher control levels than subjects of lower SES.So far, little is known if the COVID-19 pandemic affected the management of CVD risk factors, and if it widened the SES gap in CVD prevention.

WHAT THIS STUDY ADDS
⇒ Prevalence and management of CVD risk factors in Switzerland changed little during the pandemic.
Regarding the CVD risk factors management between different SES, the SES gap did not increase except for hypertension awareness.
inequalities. 12Emerging evidence suggests that the combined effect of COVID-19 and pre-existing inequalities in CVD and the social determinants of health might cause a 'syndemic effect', that is, a co-occurring synergistic pandemic exacerbating social and economic inequalities, particularly to the disadvantaged groups. 13s CVD is strongly associated with health inequalities and its risk factors are highly prevalent among socioeconomic disadvantaged groups, 14 it is likely that the COVID-19 crisis has reinforced the previously existing social inequalities.Indeed, subjects with low SES are more frequently inadequately managed for their CVD and contaminated by COVID-19. 15So far, little is known if the COVID-19 pandemic affected the management of CVD risk factors, and if it widened the SES gap in CVD prevention.Such information is vital if one wants to reduce the SES gap in health by promoting equity.Hence, we aimed to assess the effect of the COVID-19 pandemic on the socialeconomic gap regarding management of cardiovascular risk factors in the general population.Our initial hypothesis is that the socioeconomic gap increased during the pandemic.

Study setting
The CoLaus|PsyCoLaus study (https://www.colaus-psycolaus.ch/) is a population-based study investigating the epidemiology and genetic determinants of psychiatric and CVD in Lausanne, Switzerland. 16The study is mostly composed of Caucasian participants (92.6%).For this study, only data from the third follow-up was considered.Two study periods were defined: before and during the pandemic; the latter period was defined as starting after 1 March 2020.
No patient or public was involved in the drafting and conduction of the CoLaus|PsyColaus study as at that time it was not considered necessary by the investigators or the ethics committee.

Cardiovascular risk factors
In each survey, participants attended the CoLaus survey in the morning after an overnight fast and answered questionnaires, underwent a clinical examination and blood samples were drawn for analyses.Biological assays were conducted on fresh blood samples by the Clinical Laboratory of the Lausanne University Hospital (CHUV) on a Cobas 8000 (Roche Diagnostics, Basel, Switzerland).
Blood pressure (BP) was measured using an Omron HEM-907 automated oscillometric sphygmomanometer after at least a 10 min rest in a seated position, and the average of the last two measurements was used.Hypertension was defined by a systolic blood pressure (SBP) ≥ 140 mm Hg or a diastolic blood pressure (DBP) ≥ 90 mm Hg or presence of antihypertensive drug treatment or a positive answer to the question 'Did a doctor tell you that you were hypertensive?'.Awareness of hypertension was defined if the participant replied positively to the question 'Did a doctor tell you that you were hypertensive?' or if they reported any antihypertensive drug treatment.Participants with hypertension were considered as being treated if they reported any antihypertensive drug treatment.Participants treated for hypertension were considered as controlled if they had both SBP<140 mm Hg and DBP<90 mm Hg.
Diabetes was defined as a glycated haemoglobin (HbA 1 c) ≥ 6.5% (48 mmol/mol) or presence of antidiabetic drug treatment or a positive answer to the question 'Have you ever been told that you had diabetes?'.Awareness of diabetes was considered if participants replied positively to the question 'Have you ever been told that you had diabetes?' or if they reported any antidiabetic drug treatment.Participants with diabetes were considered as being treated if they reported any antidiabetic drug treatment.Participants treated for diabetes were considered as controlled if their HbA 1 c was<6.5%.
Dyslipidaemia was defined as a total cholesterol ≥6.18 mmol/L or a low-density lipoprotein (LDL) cholesterol ≥4.1 mmol/L or triglycerides ≥5.6 mmol/L or a high-density lipoprotein (HDL) cholesterol <1 mmol/L in male and <1.3 mmol/L in female 17 or presence of antilipid drug treatment or a positive answer to the question 'Have you ever been told that you had high cholesterol?'.Awareness of dyslipidaemia was considered if the participant replied positively to the question 'Have you ever been told that you had high cholesterol?' or if they reported any type of hypolipidemic drug treatment.Participants with dyslipidaemia were considered as treated if they reported any type of hypolipidemic drug treatment.Participants treated for dyslipidaemia were considered as controlled if their total cholesterol level is <5.18 mmol/L and LDL cholesterol level is <1.8 mmol/L and triglycerides level is <1.7 mmol/L or HDL cholesterol level is ≥1.5 mmol/L. 17cioeconomic status SES was defined by self-reported educational level and categorised as low (mandatory or apprenticeship), middle (high school) and high (university).

Covariates
Other data were collected by questionnaire and included gender, age, marital status (alone/couple), personal and family history of CVD, smoking (never/former/current) and alcohol consumption (yes/no).
Body weight and height were measured with participants barefoot and in light indoor clothes.Body mass index (BMI) was computed and categorised as normal, overweight (25-29.9kg/m 2 ) and obese (≥30 kg/m 2 ).

Inclusion and exclusion criteria
Participants were considered as eligible if they participated in the third follow-up.Participants were excluded if they (1) missed any data for hypertension, dyslipidaemia or diabetes and (2) missed any covariate.

Statistical analysis
Statistical analyses were conducted using Stata V. 16 for Windows (StataCorp).Participant characteristics were expressed as a number (percentage) for categorical variables or as an average±SD for continuous variables.Between-group comparisons were performed using a χ 2 or Fisher's exact test for categorical variables and a student's t-test or Kruskal-Wallis test for continuous variables.
Multivariable analyses were conducted using logistic regression for categorical outcomes, and results were expressed as OR and (95% CI).Analyses were adjusted on gender, age (continuous), education (high, middle, low), occupation (yes, no), smoking (never, former, current), BMI categories (normal, overweight, obese) and alcohol consumption (yes, no).Each CVD risk factor was also adjusted for the other two risk factors.Due to the small number of non-Caucasian participants, it was not possible to consider ethnicity in the multivariable models.Changes in the association between SES and management of CVD risk factors induced by the pandemic were assessed by including an interaction term between educational level or occupation and period.Statistical significance was considered for a two-sided test with p<0.05.

Characteristics of the participants
Out of the 3751 participants who attended the CoLaus study during the study period, 559 (14.9%) were excluded.The reasons for exclusion are indicated in online supplemental figure 1 and the bivariate analysis of the general characteristics between the included and excluded participants is summarised in online supplemental table 1.Compared with the included participants, the excluded participants were older, less frequently Swiss-born, less educated, more obese, more frequently current smokers, but less frequently drinkers.
Table 1 presents the general characteristics of the included participants who attended the study before and during the pandemic.Out of the 3192 participants, 2416 (76%) attended before and 776 (24%) attended during the pandemic.Compared with participants who attended before the pandemic, participants who attended during the pandemic were younger, more highly educated, less obese, less frequently drinkers, but slightly more current smokers.There were no significant differences in gender ratio, country of birth and history of CVD.

Prevalence and management of CVD risk factors before and during the COVID-19 pandemic
The results of the bivariate analysis of prevalence, treatment and control rates for CVD risk factors are provided in table 2. For hypertension and diabetes, prevalence did not change, while awareness decreased; no changes were found for treatment and control.For dyslipidaemia, prevalence decreased, while no changes were found for awareness, treatment and control.Moreover, no gender-specific differences regarding prevalence, awareness, control and treatment of the CVD risk factors were seen before and during the pandemic (online supplemental table 2).
The results of the multivariate analysis adjusting for gender, age, education status, alcohol consumption, smoking status, BMI categories and the presence of other CVD risk factors are provided in table 3 and figure 1. Prevalence of hypertension increased, and awareness decreased during the pandemic.For diabetes, prevalence did not change but awareness increased.For dyslipidaemia, prevalence decreased during the pandemic, but awareness did not change.No differences were found before and during the pandemic regarding treatment and control for all CVD risk factors.Association between SES and management of CVD risk factors before and during the COVID-19 pandemic Table 4 depicts the prevalence, awareness, treatment and control rates of hypertension, diabetes, and dyslipidaemia before and during the pandemic according to educational level.Prevalence of hypertension was lower among high educated participants both before and during the pandemic.Awareness was similar before the pandemic but differed during the pandemic.Treatment rates were lower among high educated participants before the pandemic, but no difference was found during the pandemic.No differences regarding control rates were found between SES groups before and during the pandemic.
Prevalence of diabetes was lower among high educated participants both before and during the pandemic with no differences between SES groups regarding awareness, treatment and control rates before and during the pandemic (table 4).
Prevalence of dyslipidaemia was lower among high educated participants both before and during the pandemic.No differences were between SES groups regarding awareness, while treatment rates were lower among high educated participants both before and during the pandemic.No differences were found between SES groups regarding control rates (table 4).
The results of the multivariable analysis of the association between SES and the management of CVD risk factors and the possible effect of the pandemic are summarised in table 5. Low educated participants tended to have a higher likelihood of hypertension compared with high educated participants with no effect of the pandemic.The likelihood of hypertension awareness decreased during the pandemic among middle educated participants (p for interaction<0.05).The likelihood of hypertension treatment was higher among middle educated participants before the pandemic and became non-significant during the pandemic, with no significant interaction with the pandemic period.No between SES differences were found regarding control of hypertension, and no changes occurred due to the pandemic (table 5).
Low educated participants had a higher likelihood of diabetes compared with high educated participants, with no effect of the pandemic.No SES differences were found in awareness, treatment and control of diabetes, and the pandemic had no impact (table 5).
No between SES differences were found regarding prevalence, awareness, treatment and control of dyslipidaemia and pandemic had no impact (table 5).Similar findings were obtained when further adjusting for occupation (online supplemental tables 3 and 4)

DISCUSSION
This study showed that prevalence and management of CVD risk factors changed little during the pandemic, and that the SES gap did not increase, except for awareness of hypertension.

Characteristics of the participants
Participants who attended the study centre during the pandemic were significantly younger than those who participated before the pandemic.The likely explanation is that on 13 March 2020, people aged 65 years and above were advised to avoid crowded places by the Swiss government as they were considered as vulnerable for the COVID-19 infection.Indeed, according to a recent study, over 90% of elderly people followed the recommendation in Lausanne.Results are expressed as number of participants (percentage).Denominator for prevalence is total sample size: denominator for awareness is the no of participants with the condition (hypertension, diabetes or dyslipidaemia); denominator for treatment is the number of participants aware of the condition; denominator for control is the number of participants treated for the condition.Between educational groups comparisons performed using χ 2 or Fisher's exact test ( §).
Participants attending during the pandemic were more frequently current smokers, a finding in agreement with studies conducted elsewhere. 19COVID-19 restrictive measures and social isolation negatively impacted the mental health of the Swiss population during the pandemic, 20 which might be a reason for the increased prevalence of smokers during the pandemic.Conversely, a study conducted in the USA reported a decline in cigarette smoking, and suggested fear of increased COVID-19 risk and economic recession as possible explanations. 21he recruiting centre was close to the Lausanne University Hospital, which was the main hub for COVID-19 admissions.As overweight, obesity and diabetes were widely highlighted in the media as risk factors for severe COVID-19, it is likely that participants with those conditions tended to avoid coming to the recruiting centre.
Prevalence of alcohol consumption considerably declined from 70% before the pandemic to nearly half (30%) during the pandemic.This decrease is consistent with the findings in 21 European countries, 22 and a likely explanation might be the closure of bars, pubs and other gather places imposed during the restrictive measures. 23evalence and management of CVD risk factors Prevalence of hypertension increased while awareness decreased during the pandemic.The increased prevalence is in line with a study in Spain, 24 where mean SBP and DBP levels increased during lockdown.Those findings could partly be due to increased smoking, 21 mental stress 20 and salty food consumption during social isolation, 25 which led to increased BP levels among participants who were not previously hypertensive.Overall, our results suggest that the lifestyle changes that occurred during the COVID-19 pandemic led to a significant increase in prevalence of hypertension, and possibly of new cases of hypertension.
The prevalence of dyslipidaemia declined during the pandemic and was further confirmed by multivariable analysis.This finding is in agreement with a study in Italy. 26he reasons for such a decline are unknown; possible explanations include the consumption of healthier foods 27 although this statement has been challenged. 28n summary, our results suggest that prevalence of dyslipidaemia decreased during the COVID-19 pandemic in Switzerland, but the exact reasons remain to be assessed.
Prevalence of diabetes did not change, but the awareness increased substantially during the pandemic.A possible explanation is that people at risk of diabetes might have checked their status more frequently, as diabetes was considered as a major risk factor for increased risk of COVID-19-related mortality. 29he outbreak of the COVID-19 pandemic led to dramatic disruptions in CVD-related services in many countries. 11Restrictive and containment measures imposed as responses to the rapidly spreading pandemic Cardiac risk factors and prevention also impacted in-person appointments, access to medicines and consequently treatment compliance in Switzerland. 30Nevertheless, it is possible that the decline of the in-person appointments in Switzerland during the pandemic might have been partly compensated by an increase in telemedicine.Indeed, telemedicine in Switzerland is relatively well developed and the use of digital services in healthcare was already increasing prior to the pandemic. 31Overall, our results suggest that the management of CVD risk factors in Switzerland changed little during the COVID-19 pandemic, and that a possible explanation would be the development of telemedicine, although this hypothesis remains to be confirmed.

Association between educational level and management of CVD risk factors before and during the COVID-19 pandemic
There is little information regarding the effect of the COVID-19 pandemic on the SES gap of CVD risk factor management.In this study, we found few differences between educational groups regarding prevalence and management of CVD risk factors, and most of the existing differences did not widen during the pandemic.The sole exception was awareness of hypertension, which decreased among middle educated participants.

Strengths and limitations
The major strengths of this study are that it is population based and was conducted using the same methodology before and during the pandemic.This study also has several limitations.First, the study was conducted in a single location in Switzerland, a country with a resilient health system and where public health measures directed against COVID-19 differed from other countries.Hence, results might not be extrapolated to other settings.Second, we cannot rule out a possible selection bias; the participants who attended during the pandemic were younger, possessed a higher educational level, exhibited lower obesity rates, less consumed frequently alcohol and showed a slight increase in current smoking tendencies (table 1).Third, it was not possible to recruit during the first lock-down period, which might have precluded some participants to attend; similarly, it is likely that participants with comorbidities were less motivated to attend, as the risk of developing severe COVID-19 was higher.Hence, it is possible that awareness, treatment and control rates be overestimated.Still, no such overestimation was observed relative to the prepandemic period and after the lockdown measures were lifted, recruitment resumed as previously.Finally, the sample size collected during the pandemic was relatively small, thus limiting statistical power.Still, to our knowledge, this is the sole study conducted in a population setting in Switzerland during the COVID-19 pandemic.

Conclusion
We conclude that the prevalence and management of CVD risk factors changed little during the pandemic.
The SES gap did not increase except for hypertension awareness.

Figure 1
Figure 1 OR of prevalence, awareness, treatment and control of cardiovascular disease risk factors between educational statues during (2020-2021) the pandemic.(Compared with prepandemic period; 2018-2019).(A) prevalence, awareness, treatment and control of hypertensive and dyslipidaemia participants during the pandemic; (B) prevalence, awareness, treatment and control of diabetic participants during the pandemic.HbA1c, glycated haemoglobin.

Table 2
Bivariate analysis of the management of cardiovascular risk factors before and during the COVID-19 pandemic, CoLaus study, Lausanne, Switzerland Results are expressed as number of participants (percentage).Denominator for prevalence is total sample size; denominator for awareness is the number of participants with the condition (hypertension, diabetes or dyslipidaemia); denominator for treatment is the number of participants aware of the condition; denominator for control is the number of participants treated for the condition.Between-group comparisons performed using χ 2 .

Table 3
Multivariable analysis of the management of cardiovascular risk factors during the COVID-19 pandemic, CoLaus study, Lausanne, Switzerland Multivariable analyses were conducted using logistic regression, and results were expressed as OR and (95% CI) using the period before the COVID-19 pandemic as reference.Analyses were adjusted on gender, age (continuous), education (high, middle, low), marital status (living with partner, living alone), smoking (never, former, current), BMI categories (normal, overweight, obese).BMI, body mass index.

Table 4
Bivariate analysis of the association between educational level and management of cardiovascular risk factors before and during the COVID-19 pandemic, CoLaus study, Lausanne, Switzerland

Table 5
Multivariable analysis of the association between educational level and management of cardiovascular risk factors before and during the COVID-19 pandemic, CoLaus study, Lausanne, Switzerland Multivariable analyses were conducted using logistic regression, and results were expressed as OR and (95% CI).Analyses were adjusted on gender, age (continuous), marital status (living with partner, living alone), smoking (never, former, current) and BMI categories (normal, overweight, obese).BMI, body mass index.Maung KK, Marques-Vidal P. Open 2023;10:e002368.doi:10.1136/openhrt-2023-002368