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The coronavirus disease 2019 (COVID-19) pandemic presented great physical and mental challenges for the residents of Wuhan (1). Elderly individuals aged 60 years or more were more susceptible and vulnerable to infectious diseases due to comparatively weaker immune functions and were a high-risk group in the pandemic. Except for effective personal protection, balanced diets and proper nutrition were effective means to maintain the immune function of the elderly. To assess the change of diet and health status of the elderly after community closure measures, we conducted a survey in Jiangxia District of Wuhan City, Hubei Province.
Considering the feasibility of field investigations, we selected two communities (A and B) in the Zhifang Sub-District, which had relatively strict management due to higher numbers of diagnosed cases compared to other sub-districts in Jiangxia District. The residents of the two communities were relatively concentrated; 11.6% of Community A were elderly individuals under social community management (where the community was managed by its own members) and 48.5% of Community B were elderly under factory group management (where residents had family members working in the factory, and this factory managed the community). Anonymous online surveys were conducted in Community A, and because some elderly individuals could not use smart phones, family members helped complete the online survey. Questionnaires in Community B were completed in person by trained team members.
A total of 117 questionnaires were completed from March 16 to 23, 2020 after 3 participants were excluded for being aged under 60 years. Overall, 35.9% of the questionnaires were completed independently, and 64.1% were completed by family members or community workers. SAS 9.4 software (SAS Institute Inc., Cary, NC, USA) was applied for statistical analysis. T-tests, analysis of variance, and chi-square tests were used to compare the differences among subgroups. Bilateral p<0.05 was considered as statistically significant.
In our survey, 45.3% of the participants were male and the ratio of genders was 1:1.21. The average age of the elderly was 72.2 ± 8.5 years (range: 60–102 years) with a similar average age in both genders. As for education, 67.5% of the elderly had schooling of 9 years or less (equivalent to junior high school or below), and 15.4% had schooling of 13 years and above (equivalent to a college or tertiary education). Among the older participants, the smoking rate was 16.2% (26.4% for men and 7.8% for women). An estimated 49.6% of the elderly suffered from chronic diseases including 69.0% having hypertension and those with diabetes, osteoporosis, and tumors accounted for 15.5%, 15.5% and 15.5%, respectively. An estimated 69.0% of surveyed individuals were chronically taking 3 or more medications. During the pandemic, 72.6% of the elderly reported that they did not pay attention to diet and nutrition, and 95.7% of the elderly did not deliberately take nutritional supplements. In our study, 21.4% of the elderly did not know their weight and 61.5% neglected waist circumference. A proportion of 15.2% in those who knew their weight reported an increased weight, while 22.2% had reductions in weight. There were statistically significant differences between gender, age, education, health status, and change of body weight between the 2 communities (p<0.05) (Table 1).
variables Community A (n=57) Community B (n=60) Total (n=117) Female (n, %) 37 (64.9) 27 (45.0)* 64(54.7) Age (mean ± sd) 69.4±8.4 74.8±7.7† 72.2±8.5 Age group (n, %) 60–69 years 31 (54.4) 18 (30.0)† 49 (41.9) 70–79 years 17 (29.8) 23 (38.3) 40 (34.2) 80 years and above 9 (15.8) 19 (31.7) 28 (23.9) Education level (n, %) Primary school and below 30 (52.6) 9 (15.0)† 39 (33.3) Junior high school 11 (19.3) 29 (48.4) 40 (34.2) Senior high school 6 (10.5) 14 (23.3) 20 (17.1) College or other tertiary education 10 (17.6) 8 (13.3) 18 (15.4) Smoking (n, %) 9 (15.8) 10 (16.7) 19 (16.2) Living with chronic diseases§ (n, %) 16 (28.1) 42 (70.0)† 58 (49.6) Hypertension (n, %) 10 (62.5) 30 (71.4) 40 (69.0) Diabetes (n, %) 4 (25.0) 5 (11.9) 9 (15.5) Osteoporosis (n, %) 5 (31.2) 4 (9.5) 9 (15.5) Tumors (n, %) 5 (31.2) 4 (9.5) 9 (15.5) Chronic use of 3 or more medications (n, %) 13 (81.2) 27 (64.3)* 40 (69.0) Paid attention to diet and nutrition (n, %) 6 (10.5) 26 (43.3)** 32 (27.4) Taking nutritional supplements (n, %) 1 (1.8) 4 (6.7) 5 (4.3) Current self-reported body weight (mean±sd) 59.4±14.2 62.3±11.0 61.0±12.5 Former self-reported body weight (mean±sd) 59.9±13.9 63.3±11.1† 61.8±12.4 Body weight change during community closure¶ No change (n, %) 15 (48.4) 30 (73.2)* 45 (62.5) Weight gain (n, %) 8 (25.8) 3 (7.3) 11 (15.2) Weight loss (n, %) 8 (25.8) 8 (19.5) 16 (22.2) Self-reported waist circumference (mean±sd) 84.9±14.3 87.7±12.3 86.8±12.9 Food sources (n, %) Local community supplies 45 (79.0) 53 (88.3) 98 (83.8) Family reserves 39 (68.4) 43 (71.7) 82 (70.1) Online purchase 21 (36.8) 8 (13.3)† 29 (24.8) Food intake reduction during community closure (n, %) 25 (43.9) 1 (1.7)† 26 (22.2) Consuming 2 meals per day or fewer during community closure (n, %) 22 (38.6) 3 (5.0)† 25 (21.4) Water intake of at least 1,500 mL per day (n, %) 8 (14.0) 17 (28.3) 25 (21.4) *: Comparison of variables between two communities, p<0.05.
†: Comparison of variables between two communities, p<0.01.
§: Chronic diseases included cardiovascular and cerebrovascular diseases, cancer, diabetes, and chronic respiratory diseases.
¶: The weight change was calculated among those who had known their body weights both before and after community closure.Table 1. Characteristics of participants in two communities during the period of community closure.
During the community closure period, the elderly reported that basic food and drink were mainly supplied by local community (83.8%) and family reserves (70.1%). There was a higher proportion of online purchasing in Community A (36.8%) than in Community B (13.3%) with statistically significant differences (p<0.01). The elderly in Community A also reported a statistically higher proportion of food reductions (43.9%) than in Community B (1.7%; p<0.01), and also a higher proportion of the elderly ate two meals per day or less in community A than community B (38.6% vs. 5.0%, p<0.01). Furthermore, only 21.4% of the elderly met the recommended 1,500 mL of daily water intake (Table 1).
About 83.8% of the elderly consumed rice or wheat products once or more per day, and 82.1% consumed fresh vegetables more than one time a day. The proportion of the elderly who consumed red meat and poultry once a week or more was 69.2%. The frequency of egg consumption of the elderly was 63.3% of at least once a day and 28.2% of 1–6 times a week. However, the proportions of elderly consuming soybeans, milk, and aquatic food products (including freshwater fish, marine fish, shrimp, crab, shellfish and other animal aquatic products excluding seaweed, kale, etc.) less than once a week were 73.5%, 61.6%, 60.6%, respectively. Red meat and poultry intake frequency of more than once a day among males was significantly higher than that in female (52.8% vs. 34.4%, p<0.01). Potatoes consumption frequency of more than once per day among individuals aged 80 years and above was significantly lower than that of individuals aged 70–79 years and individuals aged 60–69 years (10.7%, 20.0%, 16.3%; p<0.05). However, there were no statistically significant differences of intake frequency of specific foods between the elderly in better health status and those living with chronic diseases. When compared with before community closures, the proportions of elderly consuming dramatically less aquatic food products, soybeans, and fresh fruit after community closures were 70.9%, 70.9%, and 53.0%, respectively. Subgroup analysis showed that the consumption of rice/wheat products and coarse grains was significantly reduced among females than in males ( rice/wheat products: 21.9% vs. 5.7%, coarse grains: 46.9% vs. 24.5%, p<0.05), but healthy individuals consumption of eggs, red meat, and poultry were reportedly more significantly reduced than in individuals with chronic diseases (eggs: 22.0% vs. 6.9%; red meat and poultry: 44.1% vs. 32.8%; p<0.05)(Table 2).
Food items Gender (%) Age group (%) Healthy status† (%) Total (%) Male Female 60–69 years 70–79 years 80 years and above Yes No Rice/wheat products ≥ once/day 92.5 76.6 79.7 82.5 92.9 83.1 84.5 83.8 1–6 times/week 7.5 12.5 16.3 10.0 − 11.9 8.6 10.3 1–3 times/month − 4.7 2.0 5.0 − 3.4 1.7 2.6 ≤ once/month − 6.2 2.0 2.5 7.1 1.6 5.2 3.3 Reduction 5.7 21.9§ 14.3 17.5 10.7 15.3 13.8 14.5 Coarse grains ≥ once/day 24.5 17.1 22.5 17.5 21.4 22.0 19.0 20.5 1–6 times/week 20.8 26.6 16.2 37.5 17.9 15.3 32.8 23.9 1–3 times/month 17.0 26.6 28.6 15.0 21.4 22.0 22.3 22.2 ≤ once/month 37.7 29.7 32.7 30.0 39.3 40.7 25.9 33.4 Reduction 24.5 46.9§ 36.7 45.0 25.0 37.3 36.2 36.8 Potatoes ≥ once/day 17.0 15.6 16.3 20.0 10.7§ 17.0 15.5 16.2 1–6 times/week 39.6 40.7 44.9 47.5 21.4 37.3 43.1 40.2 1–3 times/month 30.2 28.1 28.6 27.5 32.1 30.5 27.6 29.1 ≤ once/month 13.2 15.6 10.2 5.0 35.8 15.2 13.8 14.5 Reduction 34.0 39.1 36.7 40.0 32.1 44.1 29.3 36.8 Fresh vegetables ≥ once/day 88.7 76.6 83.7 75.0 89.3 81.4 82.8 82.1 1–6 times/week 11.3 15.6 14.3 20.0 3.6 15.3 12.1 13.7 1–3 times/month − 6.3 2.0 5.0 3.6 3.3 3.5 3.3 ≤ once/month − 1.5 − − 3.5 − 1.6 0.9 Reduction 32.1 34.4 30.6 40.0 28.6 30.5 36.2 33.3 Fresh fruits ≥ once/day 32.1 26.6 32.7 22.5 32.1 28.8 29.3 29.1 1–6 times/week 43.4 32.8 42.9 37.5 28.6 33.9 41.4 37.6 1–3 times/month 18.9 29.7 20.4 27.5 28.6 28.8 20.7 24.8 ≤ once/month 5.6 10.9 4.0 12.5 10.7 8.5 8.6 8.5 Reduction 45.3 59.4 51.0 60.0 46.4 52.5 53.5 53.0 Eggs ≥ once/day 71.7 56.3 63.3 62.5 64.3 57.6 69.0 63.3 1–6 times/week 24.5 31.3 28.6 27.5 28.5 33.9 22.4 28.2 1–3 times/month 1.9 9.4 6.1 7.5 3.6 5.1 6.9 6.0 ≤ once/monthh 1.9 3.0 2.0 2.5 3.6 3.4 1.7 2.5 Reduction 7.6 20.3 16.3 17.5 7.1 22.0 6.9§ 14.5 Aquatic food products** ≥ once/dayy 11.3 9.4 10.2 10.0 10.7 11.9 8.6 10.3 1–6 times/week 35.9 23.4 30.6 25.0 32.1 32.2 25.9 29.1 1–3 times/month 39.6 39.1 38.8 42.5 35.8 33.9 44.8 39.2 ≤ once/month 13.2 28.1 20.4 22.5 21.4 22.0 20.7 21.4 Reduction 67.9 73.4 71.4 75.0 64.3 66.1 75.9 70.9 Red meat and poultry ≥ once/day 52.8 34.4¶ 42.9 40.0 46.4 35.6 50.0 42.7 1–6 times/week 34.0 20.3 30.6 22.5 25.0 30.5 22.4 26.5 1–3 times/month 7.6 31.3 20.4 20.0 21.4 18.6 22.4 20.5 ≤ once/month 5.6 14.0 6.1 17.5 7.2 15.3 5.2 10.3 Reduction 34.0 42.2 40.8 37.5 35.7 44.1 32.8§ 38.5 Milk ≥ once/day 20.8 9.4 14.3 7.5 25.0 11.9 17.2 14.5 1–6 times/week 22.6 25.0 22.5 25.0 25.0 20.3 27.6 23.9 1–3 times/month 20.8 23.4 26.5 25.0 10.7 20.3 24.1 22.2 ≤ once/month 35.8 42.2 36.7 42.5 39.3 47.5 31.1 39.4 Reduction 24.5 45.3 38.8 40.0 25.0 39.0 32.8 35.9 Soybeans ≥ once/day 9.4 3.1 6.1 2.5 10.7 6.8 5.2 6.0 1–6 times/week 24.5 17.2 22.5 17.5 21.4 23.7 17.2 20.5 1–3 times/month 39.6 32.8 30.6 42.5 35.7 33.9 37.9 35.9 ≤ once/month 26.5 46.9 40.8 37.5 32.2 35.6 39.7 37.6 Reduction 69.8 71.9 73.5 80.0 53.6 64.4 77.6 70.9 *: The proportion of the elderly whose food intake frequency less than they did before community closure.
†: Healthy status was defined as whether the elderly had living with chronic diseases.
§: Comparison of each variable in different subgroups, p<0.05.
¶: Comparison of each variable in different subgroups, p<0.01.
**: Aquatic food products included freshwater fish, marine fish, shrimp, crab, shellfish and other animal aquatic products excluding seaweed, kale, etc.Table 2. Intake frequency of specific foods and reductions* among elderly participants during the period of community closure.
Table 3 showed that 85.5%, 83.8%, 79.5%, 73.5%, 70.9%, and 60.7% of the elderly consumed milk, potatoes, coarse grains, soybeans, fresh fruits, and aquatic food products lower than recommended levels. Females also showed much higher rates of not consuming recommended amounts of rice/wheat products, red meat, and poultry when compared to males (rice/wheat products: 23.4% vs. 7.6%; red meat and poultry: 45.3% vs. 13.2%).
Food items Gender Age group Healthy status† Total Male Female 60–69 years 70–79 years 80 years and above Yes No Rice/wheat products 7.6 23.4§ 20.4 17.5 7.1 17.0 15.5 16.2 Coarse grains 75.5 82.8 77.6 82.5 78.6 78.0 81.0 79.5 Potatoes 83.0 84.4 83.7 80.0 89.3 83.1 84.5 83.8 Fresh vegetables 11.3 23.4 16.3 25.0 10.7 18.6 17.2 18.0 Fresh fruits 67.9 73.4 67.4 77.5 67.9 71.2 70.7 70.9 Eggs 28.3 43.8 36.7 37.5 35.7 42.4 31.0 36.8 Aquatic food products¶ 52.8 67.2 59.2 65.0 57.1 55.9 65.5 60.7 Red meat and poultry 13.2 45.3** 26.5 37.5 28.6 33.9 27.6 30.8 Milk 79.3 90.6 85.7 92.5 75.0 88.1 82.8 85.5 Soybeans 66.0 79.7 71.4 80.0 67.9 69.5 77.6 73.5 *: the recommended intake frequency of rice/wheat products, coarse grains, potatoes, fresh vegetables, fresh fruits, eggs, and milk were more than once a day, while intake of aquatic products, red meat, poultry, and soybeans of more than once a week were defined as meeting the recommendations.
†: Health status was defined as whether the elderly were living with chronic diseases.
§: Comparison of each variable in different subgroups, p<0.05.
¶: Aquatic food products included freshwater fish, marine fish, shrimp, crab, shellfish and other animal aquatic products excluding seaweed, kale, etc.
**: Comparison of each variable in different subgroups, p<0.01.Table 3. Elderly participants failing to reach the recommended intake levels of specific foods during the period of community closure* (%)
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This investigation demonstrated that dietary nutrition status of the elderly was affected during the COVID-19 pandemic in Wuhan as their consumption of aquatic food products, soybeans and fresh fruits decreased significantly. Furthermore, unreasonable and unbalanced diet structure combined with decreased physical activity will increase the risk of chronic diseases. Therefore, the elderly should maintain balanced diet as well as an active lifestyle during the pandemic.
During the period of community closure in Wuhan, early of foods reservs such as rice, flour, oil, vegetables, eggs, meats, and poultry were often prioritized at the family level. These basic foods provided adequate energy and moderate levels of protein to prevent severe energy-protein malnutrition from occurring in the short term. In addition, community food supplies were a complementary addition for household food stocks. But due to different community management, there were differences in the variety and quantity of the food supply, which potentially influenced the food intake of the elderly. Due to limits in the food supply and insufficient intake of fresh fruits, soybeans, and aquatic food products, the elderly inevitably experienced a lack of high-quality protein, calcium, vitamins, and essential fatty acids, so increasing the variety of available food should be a priority as the communities return to normalcy. In addition, high-quality protein plays an important role in improving immunity of the elderly during the pandemic (2). Fish, poultry, eggs, milk, lean meat, and soybean products are primary sources of high-quality protein, but marinated/processed fish and meat products should be avoided for the potential of increasing cardiovascular disease risk in the elderly.
Elderly individuals often suffer from hypertension, diabetes, or other non-communicable cardiovascular diseases and must take multiple medications regularly. They paid more attention to their health in case of emergencies, so drug stockpiles and medical resources should always be prioritized by themselves or by the community (3). However, their nutritional status was often neglected, and food intake correspondingly decreased, especially when combined with digestive dysfunction and loss of appetite during the pandemic. For elderly with hypertension or diabetes, adequate coarse grains, vegetables, and soybeans could benefit for their blood glucose and blood pressure (4-5). Chinese dietary guidelines also recommended that a daily diet should contain an adequate amount of these plant-based foods (2).
There are some limitations in our study. First, although there was variation in age, gender, education, lifestyles, and other characteristics of the elderly involved in our study, findings from this survey were not representative of the elderly living in closed communities in Wuhan. Second, given the self-reported information nature of this survey, the results were subjected to some level of recall bias or mistakes. Third, data in this study were based on information provided by participants, so the results were also influenced by some level of subjectivity. Nevertheless, the study reflected the nutritional and health status of the elderly during the COVID-19 pandemic and can be used to inform elderly individuals’ health maintenance and promotion in Wuhan.
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