Introduction

The Novel Coronavirus disease, COVID-19, posed an unprecedented threat to humanity since its detection in December 2019. The virus caused an infection with high contagiousness and potential for rapid spread, which led to significant morbidity and mortality, with over 100 million cases worldwide. Several countries, including the USA, imposed national lockdowns to decrease transmission and reduce the resulting damage. In New York, about two weeks after the detection of the first case of the disease on March 1st 2020, the government issued a stay-at-home order (also known as the New York state on PAUSE order). This period of isolation lasted approximately four months and was followed by a phased re-opening of businesses and re-initiation of activities in the state [1]. Significant economic, social, and health related consequences were noted as a result. Pursuing work from home and the closure of gyms led to several individuals spending significant periods of time indoors in a sedentary manner with a decline in physical activity levels and a worsening of dietary habits. There was decreased access to healthcare for non-emergent issues and pharmacies to obtain medication. A combination of the above factors could worsen lifestyle-related chronic diseases like type 2 diabetes mellitus, hypertension, and obesity. A study involving obese patients from Italy determined that patients gained an average of 1.51 kg after a month-long quarantine and that their mean BMI rose by 0.58 kg/m2 [2]. An observational study on the effect of the lockdown on glycemic control in patients with T2DM in Central India showed a worsening of hyperglycemia and the requirement for additional medication for optimal control [3].

However, a hospital-based cross-sectional study from Southern India showed no change in the diet, physical activity, and glycemic control for most individuals with T2DM [4]. A study exploring similar associations in Turkey too found statistically insignificant worsening of glycemic control and weight gain in study participants [5].

While some data exists regarding changes in body weight and blood glucose levels during the COVID pandemic in patients with Type 1 Diabetes in the US, there is a paucity of data regarding the same in individuals with type 2 diabetes in an outpatient setting. This study aims to compare changes in glycemic control and body weight in patients presenting for health maintenance visits to a primary care clinic in Manhattan during the years before the onset of the pandemic and in the years after its onset.

Materials and methods

Ethical approval was obtained from the Institutional Review Board (RNI01016), and permission for research was obtained from the participating clinic site.

We conducted a single-site observational study at a Federally Qualified Health Center (FQHC) in New York City. Patients at or over the age of 18, with at least one health maintenance visit or follow-up visit to the health center between the years 2015 and 2020 and with at least one recorded measurement of Hemoglobin A1c and BMI, were included in the study.

Data, including relevant patient demographic details, BMI measurements for patients were gathered using the electronic medical record database at the clinic site for the years beginning from 2015 to 2019 to obtain baseline information regarding trends in the annual change of body weight and glycemic control. Hemoglobin A1c measurements were obtained starting in 2018, due to lack of reliable stored data in the years prior. Similar data were extracted for the years 2020 and 2021 after the onset of the pandemic. All data was then deidentified, with patient identifiers being replaced with unique study-specific identifiers and stored in a password protected encrypted database.

Two sample T-tests were used to compare the differences in annual changes in hemoglobin A1c prior to the onset of the pandemic and after its start. The slopes of change in BMI from prior to, to after the pandemic were estimated and compared using a generalized linear model. Statistical analysis was carried out using SAS V9.4.

Results

973 females (69%) and 432 males (31%) between the ages of 19 and 103 years were included in the study. The mean age of participants was 61 ± 17 years.

The average annual change in HbA1c from 2018 to 2019 versus 2019 to 2020 was not significantly different (23% difference, p = 0.23). However, after the pandemic, there was an increase of 103% in the annual change in average HbA1c from the years prior to the onset of the pandemic versus from early 2020 to 2021, after its onset (p < 0.005). These results are tabulated in Table 1. While this is statistically significant, the clinical relevance of this trend will have to be determined.

Table 1 Change in Hemoglobin A1c pre and post the onset of the COVID-19 pandemic
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Mean BMI increased over the pandemic although this was not statistically significant. The slope of the annual change in mean BMI over five years prior to the pandemic was − 0.09 (p = 0.2455), while the slope of change in BMI after the onset of COVID-19 was 0.31 (p = 0.4905). The difference between the two slopes is 0.48 (p = 0.37). No statistically significant differences were noted between females and males. The difference between the two slopes is 0.34 (p = 0.5494) in males and 0.56 (p = 0.4441) in females, indicating no gender related differences. Results are tabulated in Table 2.

Table 2 Average BMI pre and post the onset of the COVID-19 pandemic
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Discussion

The COVID-19 pandemic ushered in significant changes in the lifestyles of individuals across the globe due to socio-economic restrictions imposed to curb the spread of the infection. The period of strictly imposed constraints on social interactions and public activities commonly referred to as the “lockdown,” led to an increase in the total duration of time spent indoors, especially at home, with altered levels of physical activity, changes in diet, decreased access to healthcare and increases in mental health stressors [6,7,8].

Lack of access to non-essential health care services, including pharmacies, compounds difficulties in appropriately managing these lifestyle disorders. A combination of the above factors worsens health outcomes related to chronic metabolic diseases. We postulated that as a result, patients would likely experience an increase in body weight as indicated by Body Mass Index and elevated blood glucose levels as indicated by an elevation in glycated hemoglobin (HbA1c) via the increased formation of advanced glycation end products.

A study involving obese patients in Italy reported an average weight gain of 1.51 kg with a mean increase in BMI by 0.58 kg/m2 after quarantine, extending for about a month [2]. These findings were noted to be significantly associated with lower education levels, self-reported anxiety/depression, as well as poor food choices among patients [2]. The study also noted decreased exercise and non-exercise physical activity levels in most participants (79%), as compared to pre-pandemic levels [2].

In addition, even though all patients received personalized nutritional advice, a significant number reported unhealthy dietary habits, such as eating larger quantities of food in 40% of participants, increased frequency of consuming sweet foods and snacks in 50% and 30% of participants respectively and decreased consumption of fresh produce including fruit and vegetables in 18% of participants. This indicates that behavioral factors, rather than lack of knowledge or access to foods, prevent patients from adhering to healthy eating practices.

A study in France revealed that certain unfavorable dietary and activity changes occurred during the lockdown [9]. These included decreased physical activity and increased sedentary time, as reported by over half of the participants; 53% and 63% respectively. In addition, around 38% of participants reported unfavorable dietary habits including increased snacking, decreased consumption of fresh food and concurrent increased consumption of processed, high calorie-low nutrient density foods. Healthy nutritional choices were reported by only close to 20% of participants. However, 19% of participants were found to engage in increased physical activity and 40% of participants reported increased consumption of home cooked meals, suggesting favorable lifestyle modifications. In addition, 35% of the participants were found to have gained weight (Mean weight gain 1.8 kg ± SD 1.3 kg), 23% to have lost weight (mean weight loss 2 kg ± SD 1.4 kg), while body weight remained stable in 42% of the participants [9].

An observational study on the effect of the lockdown on glycemic control in patients with Type 2 Diabetes Mellitus (T2DM) in Central India indicated that 39.16% of patients reported worsening of hyperglycemia, mainly after meals, requiring the addition of medications for control of blood sugars [3]. The highest correlations with worsening glycemic control were observed between psychological stress, followed by changes in exercise regimens and dietary habits [3].

However, some studies have shown no negative changes or changes pointing towards transition to healthier lifestyles. A hospital-based cross-sectional study of 110 patients with type 2 diabetes mellitus from Southern India showed no significant differences among most participants with respect to their diets, physical activity levels or glycemic control [4]. More than 80% of patients were noted to have no significant change in their physical activity pattern as well as overall adherence to prescribed diets. Only 10% of patients reported unavailability of medications or medication non-compliance, whereas 90% had access to and used their medications appropriately during the lockdown. There was no noted statistically significant difference in the mean HbA1c before (8.2 ± 1.3%) and after (8.12 ± 1.6%) the lockdown or in the mean body weight before (71.5 ± 14.8 kg) and after (71.8 ± 13.6 kg) the lockdown [4].

A study exploring similar associations in Turkey too found statistically insignificant worsening of glycemic control and weight gain in study participants [5]. They attributed this to their patients being less obese and having higher levels of health literacy regarding the management of their chronic metabolic disorders.

Our study depicts worsened glycemic control with no significant changes in BMI. Most of the patients visiting this center belong to lower socioeconomic strata, and a significant percentage are uninsured. This results in difficulty in accessing nutrient-dense foods, facilities for physical activity, and a lack of available time to dedicate to exercise. We also postulated that many patients faced barriers in accessing healthcare providers and pharmacies, compounding the problem.

A study from Italy showed that a large section of the population suffered delays and interruptions of medical services [10]. 32.4% of people faced a delay of a scheduled Medical Service (MS) by a provider, while 13.2% refused to access scheduled MS for fear of contracting COVID-19. 6.5% of participants avoided healthcare services while experiencing an acute illness, and 1.5% of the population avoided visiting the Emergency Department when in need. 5.0% of people took medications without consulting any physician, making them more prone to self-medication [10].

A recent study from the United States showed that 43% of patients missed routine preventative care appointments due to the pandemic, and more than a third of adults did not receive recommended screening procedures during the same period [11].

Conclusions

Given the need for limited data of this type in the United States and conflicting data from other parts of the world, it can be concluded that there is a need to explore changes in healthcare outcomes in patients with non-communicable diseases occurring due to downstream effects of the pandemic. There is indeed a pressing requirement to provide continued support to patients with chronic disorders through telemedicine, access to medications, improved access to laboratories or facilities for the collection of samples from home as well as continued emotional support during a pandemic to prevent acute and chronic complications and to decrease the burden on the healthcare system.

Limitations

We recognize that there was a significant reduction in the number of patients who attended routine preventive care and follow up appointments in the aftermath of the pandemic, which could have affected the results of our study. Our study merely explored changes in health-related outcomes in patients pre-pandemic and post-pandemic but did not examine changes in probable etiologic factors like diet, exercise and stress levels in patients. Our study was not equipped to explore differences among different gender for glycemic control and differing age groups or differing racial and ethnic backgrounds and socioeconomic strata for all metabolic parameters studied. In addition, it is a cross-sectional study and cannot establish the causation of worsened health-related outcomes to changes secondary to the pandemic.