Weather and Human Conception

Abstract

A statistically significant inverse relationship was found between mean monthly temperature 9 mo. prior to delivery and 7,312 live births in a midwestern community. A curvilinear relationship fit the data more closely than a linear one, suggesting both extremely cold and hot weather were related to the birth rate 9 mo. later. Illegitimate and legitimate births followed nearly the same pattern. Marriages and the number of births 9 or even 10 mo. later were not related. Apparently the weather, particularly cold' weather, has a powerful influence on behavior resulting in conception.

The “Christmas Effect” and Other Biometeorologic Influences on Childbearing and the Health of Women

“…A curvilinear relationship fit the data of this study more closely, suggesting that extremely hot and cold weather is related to birth rates, with cold weather having the greatest effect. Sherrets (1979) noted that births to married and unmarried women followed nearly the same pattern. Brundtland and Liestol (1982) described seasonal variations in menstrual cycles and menarche, suggesting that female physiology provided an explanation for the seasonality of births.…”

“…Lajinian, Hudson, Applewhite, Feldman, and Minkoff (1997), in a historic cohort study conducted at a Brooklyn, New York, hospital from March 21, 1993, through March 20, 1994, found that a high heat index is associated with an increased incidence of preterm labor. Sherrets (1979) also concluded that there was a significant relationship between the mean monthly temperature 9 months before delivery and 7,312 live births in a midwestern community. A curvilinear relationship fit the data of this study more closely, suggesting that extremely hot and cold weather is related to birth rates, with cold weather having the greatest effect.…”

The Association between Daily Weather and Daily Shopping Patterns

“…Cawthorne (1998a) points out that weather often determines the starting and ending points of a merchandising season, as well as mid-season peaks, and can not only shift a season but make it longer or shorter, whilst Fox (1993) notes that weather affects overall volume or store traffic. Meteorological variables have been linked to a diverse range of human behaviours (e.g., Robbins et al, 1972;Banziger and Owens, 978;Sherrets 1979;Cunningham, 1979;Jorgenson, 1981a;Sanders and Brizzolara, 1982;Howarth and Hoffman, 1984;Albert et al, 1991;Cohn, 1993). Researchers have also hypothesised that mood state mediates the relationship between weather and behaviour (e.g., Bell and Baron, 1976a;1976b;1977;Cunningham, 1979;Schneider et al, 1980;Bell, 1981;Persinger and Levesque, 1983;Howarth and Hoffman, 1984).…”

Too many simple clerical scoring errors: The Rey Figure as an example

“…From a clerical standpoint the Rey Figure is simple to score, unlike the Wechsler scales in which Sherrets, Gard, and Langner (1979) found that 89.5% of 200 WISC protocols contained at least one clerical error and 46.5% contained more than one clerical error, and Levenson, Golden-Scadoto, Aiosa-Karpos, and Ward (1988) found that 57% of 162 WISC-R protocols contained clerical errors. Because the Rey Figure's scoring protocol is short and has a simple structure, near zero percent clerical errors were expected.…”