The data presented on the current study are part of the data taken from a survey carried out by the Israel Ministry of Health, over an 18-month period, between July 2005 and December 2006.
The target population included Israeli citizens aged 65 and above, living in the community (in their own homes or sheltered housing), who have resided in the country for at least 1 year.
Adults not living in their own homes in the community for the following reasons: being out of the country for 6 months or more, hospitalization for more than 6 months, hospitalization in a psychiatric institution, hospitalization in a long-term care institution or an institution for the mentally fragile or older adults with significant cognitive reduction according to the Mini Mental State Examination (MMSE) score adjusted for age and education, and immigrants who arrived in Israel after December 31, 2003. In total, after the exclusion procedure (which is detailed in Netz et al. ), 1,663 individuals, aged 74.31 (±6.05) years old, took part in the study—799 men and 864 women.
The survey was approved by the Ethics Committee of the Chaim Sheba Medical Center and the Ministry of Health. Each interviewee signed an informed consent form for the questionnaire and for the measurement of anthropometric parameters.
Survey tools and organization
A personal, face-to-face interview was conducted in the interviewee’s home using a structured questionnaire and a 24-h recall questionnaire. The questionnaire included demographic details and questions on health status, functional status, cognitive state, use of medications and nutritional supplements, physical activity, smoking status, and eating and dieting patterns. Health status was determined based on reported chronic illnesses. The chronic illnesses list included nine illnesses/conditions: heart disease, lung disease, stroke, renal disease, cancer, diabetes, hypercholesterolemia, hypertension, and osteoporosis. The number of illnesses/conditions was recorded. Smoking status was determined based on three options: currently smoking, smoked in the past, and never smoked. Eating and dieting patterns were based on nutrient data collected, and nutrient intakes, including calcium, were calculated using the Tzameret dietary analysis program, which contains the “BINAT” nutrient database. This program was developed by the Nutrition Department of the Ministry of Health. At the end of the interview, measurements of anthropometric parameters were taken.
The measurements were carried out twice (and the average was calculated) according to a protocol and included standing height, weight, and waist circumference. All measurements were carried out in light clothing. Weight and height were measured without shoes, although if the interviewee refused to remove his/her shoes, this was noted, and then 2 cm were subtracted from the height measurement.
Weight measurement was carried out using an analog scale suitable for weighing up to 130 kg, with accuracy to 0.5 kg. The scales were placed on an uncarpeted floor and calibrated before weighing. If the measurements differed by more than 1.0 kg, a third measurement was carried out.
This was measured using a flexible tape that could measure up to 150 cm, at the narrowest part of the torso, where a fold is created when bending sideways. If the two measurements differed by more than 5 mm, a third measurement was carried out.
This was measured using a spring-coil measuring tape. A rigid aluminum angle was used to determine the meeting point of the top of the skull with the wall/door, and stickers were used to mark the height. If the two measurements differed by more than 5 mm, a third measurement was carried out.
BMI was calculated by the formula: weight (kg)/height (m)2.
Assessment of physical activity
The physical activity questionnaire used in the current study was based on a standard questionnaire used previously in an adult (aged 25–64) population study by the Israel Center for Disease Control performed together with the Food and Nutrition Services. Participants were asked about their physical activity habits in two sets of questions; one set referred to intensive activity (participation in energetic physical activity that “makes you breathe harder or puff and pant”), and the other to leisure-type physical activity. Participants reported the frequency, duration (months or years), and average length of activity sessions. In addition, they were asked to report the time devoted to specific activities (walking outside or on a treadmill, jogging, swimming, bike riding or stationary cycling, light exercise such as yoga, body shaping, and strength training in a fitness room). Based on recommendations from the American Heart Association , the ACSM  and the DHHS , regarding aerobic exercise, participants were divided into three groups according to level of physical activity (for further details see Netz et al. ):
Sufficiently active—those who were involved in moderate leisure-type physical activity for at least 150 min a week or in intensive activity for at least 75 min a week, or a combination of the two.
Insufficiently active—those who were involved in physical activity but for a lesser amount of time than the above.
Inactive—those who reported no activity or activity less than once a week.
As there are anthropometric differences between men and women, all analyses were conducted separately for each gender. Analyses were performed in three phases:
One-way ANOVAs were conducted for assessing differences between the activity groups on the following demographic and health variables, which are known to relate to anthropometric parameters: age, number of illnesses, number of medications, and calcium intake [2, 3, 6, 7, 9, 10, 20, 25]. A chi-square analysis was conducted on percent of smokers in each group.
One-way ANOVAs were conducted for assessing differences between the activity groups on the following anthropometric measurements: weight, waist circumference, height, and BMI. Bonferroni post hoc procedure was used for assessing the differences between the activity groups (alpha = 0.05).
Two-step regressions were conducted to assess the contribution of demographic and health variables (step 1) and physical activity (step 2) to the variability of each anthropometric parameter (step 1).