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Introduction The coronavirus pandemic has disproportionately negatively affected the ultraorthodox in Israel. Their unique characteristics and slow adoption of preventative health guidelines resulted in a significant increase in morbidity and mortality. To lower these rates, health and government authority figures employed methods to change the ultraorthodox community health behaviors. Methodology This study utilizes the ACCESS model for transcultural nursing to analyze the response by authorities to high infection rates in the large ultraorthodox community in city of Beit Shemesh during the first wave of the outbreak (through early May). Results The authorities employed all model components to varying degrees and found moderate success in changing health behaviors of the ultraorthodox. Discussion Employing the ACCESS model as a response to the health care crisis among the ultraorthodox community in Beit Shemesh led to some success in increased compliance, thus lowering morbidity rates. However, not establishing strong respect and rapport hindered the process.

Research indicates that mortality rates are lower among the religious. Israeli ultra‐orthodox Jews, called Haredim, have characteristics distinguishing them from the rest of the Jewish population in Israel. These include lower socioeconomic status, higher fertility rates and rates of young marriage, and isolation from the general population. Our retrospective cohort study aims to determine the difference in mortality rates between Haredi and non‐Haredi Jews in Israel. We collected data on sociodemographic variables, religious lifestyle, and all‐cause mortality for 1,230,636 Jewish Israelis (62,674 Haredim) between 1996 and 2016. Using Cox regression and adjusted Kaplan‐Meier curves, we constructed models to evaluate the relationship between identifying as Haredi and mortality. The mortality rate was significantly lower among the Haredi population compared to the non‐Haredi population (5.0 percent vs. 8.2 percent). After adjusting for sex, age, marital status, number of children, education, and socioeconomic status, we still found a higher mortality rate among non‐Haredim compared to Haredim (HR = 1.596; 99 percent CI = 1.519, 1.678). While causal mechanisms could not be analyzed in this study, a likely cause is increased social, psychological, and religious resources, highlighting the need to consider factors other than socioeconomic status when studying religious and other groups with other forms of capital.

Breast cancer is a leading cause of death. There are a number of risk factors for breast cancer mortality including parity, age, ethnicity, genetic history, and place of residence. This study examined the disparities in breast cancer-related mortality rates among women from urban areas compared to rural areas in Israel. This was a retrospective, follow-up study on mortality from breast cancer among 894,608 Israeli women born between the years of 1940 and 1960. Data was collected from the Israeli Central Bureau of Statistics, the Population Authority, the Education Ministry, and the Health Ministry. Over 80% of women lived in urban areas. A higher incidence of mortality from breast cancer in Israel was found among urban women compared to rural women (1047.8/100,000 compared to 837/100,000, respectively). Even after adjusting for sociodemographic variables, higher mortality rates were found among women from urban areas in Israel compared to women from rural areas in Israel. It is believed that environmental factors can partially explain the geographic variation of breast cancer incidence, and that breast cancer incidence is likely a complex interaction between genetic, environmental, and health factors.

The COVID-19 pandemic has imposed barriers to a healthy lifestyle, especially for older adults who are considered to be at a high-risk of infection. This study examined the associations between negative changes and the self-classification to COVID-19 risk level among physically active older adults who are members of a nationwide health club chain. A cross-sectional digital survey was sent to 19,160 older adults (age ≥ 65). The data collected included information on the subjects’ self-classification to the COVID-19 high-risk group (HRG) and changes in physical activity (PA), body weight, and smoking habits since the outbreak. Logistic regression models were used to investigate the associations between the dependent variables of ‘experienced a negative change’ and the independent variables. Of the 1670 survey respondents, 78.3% classified themselves as COVID-19 HRG. Over half of the respondents reported a reduction in PA hours, 26.6% reported weight gain, and 17.7% of smokers increased their amount of smoking. A self-classification to the HRG was associated with 1.46 (95%CI 1.10–1.93, p < 0.009) and 1.67 (95%CI 1.21–2.31, p < 0.002) greater odds for reduced hours of exercise and weight gain compared to the not high-risk group, respectively. Decision makers should consider how policies may cause barriers to a healthy lifestyle and develop risk communication strategies to encourage positive health-related behaviors, even during a pandemic.